5th International Conference on Reanalysis (ICR5) · 2017-11-03 · data for climate reanalyses Leopold Haimberger (University of Vienna) 2.30–2.45pm O.05 The Copernicus Climate

5th International Conference on Reanalysis (ICR5) 13–17 November 2017, Rome

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Contents

2ECMWF | 5th International Conference on Reanalysis (ICR5) 2017

It is our pleasure to welcome the reanalysis community at the 5th International Conference on Reanalysis (ICR5). We are delighted that we are all able to come together in Rome. This five-day international conference is the worldwide leading event for the continuing development of reanalysis for climate research, which provides a comprehensive numerical description of the recent climate on a global scale. Climate reanalysis data is used by public services, companies and organisations. It provides the means to assess climate trends and the changing climate.

ICR5 provides us the opportunity to review progress and discuss future plans in key areas, including:

• Status of current production systems

• Observation rescue activities

• Developments in observational databases

• Developments in data assimilation

• Applications, user requirements and feedback

• Plans for future reanalyses

Climate research has benefited over the years from the continuing development of reanalysis. As reanalysis datasets become more diverse (atmosphere, ocean and land components), more complete (moving towards Earth-system coupled reanalysis), more detailed, and of longer timespan, community efforts to evaluate and intercompare them become more important.

The conference brings together reanalysis producers, observation providers, numerical modellers and the user community to review current reanalysis activities and to discuss user needs for future reanalyses.

Through this conference, we aim to assess the merits and review the progress in reanalyses, to monitor climate variations and support policy makers to develop adaptation policies, and to provide complementary information to other climate sources.

The Scientific Organizing Committee, co-chaired by Roberto Buizza (ECMWF) and Paul Poli (Météo-France), has structured the conference around five main topics.

•Status and plans for future reanalyses Global and regional production, inclusive

of all WCRP thematic areas: atmosphere, land, ocean and cryosphere – Session organisers: Mike Bosilovich (NASA GMAO), Shinya Kobayashi (JMA), Simona Masina (CMCC)

•Observations for reanalyses Preparation, organisation in large

archives, data rescue, reanalysis feedback – Session organisers: Marie Doutriaux-Boucher (EUMETSAT), Pierre-Philippe Mathieu (ESA), Nick Rayner (Met Office)

•Methods for reanalyses Data assimilation, Earth-system

coupling, uncertainty estimation, challenges specific to regional reanalyses – Session organisers: Magdalena Alonso-Balmaseda (ECMWF), Gil Compo (CU/CIRES & NOAA), Dick Dee (C3S), Zhiquan Liu (NCAR & CMA)

•Evaluation of reanalyses Comparisons with observations,

other types of analysis and models, inter-comparisons, diagnostics – Session organisers: Franco Desiato (ISPRA), Masatomo Fujiwara (Hokkaido University), Sonia Seneviratne (ETH), Adrian Simmons (ECMWF)

•Applications of reanalyses Generating time-series of Essential

Climate Variables for climate monitoring, validation of third-party products, environmental planning and policies, adaptation and mitigation policies, climate services, industry, scientific research and education, other applications – Session organisers: Andrea Kaiser-Weiss (DWD), Carolin Richter (WMO), Michel Rixen (WCRP), Jean-Noël Thépaut (C3S)

The 5th International Conference on Reanalysis (ICR5) is organised by ECMWF’s Copernicus Climate Change Service (C3S) and the WMO World Climate Research Programme (WCRP).

We look forward to meeting you!

The ICR5 Organisation Committee

We would like to thank all our partners and supporters of the 5th International Conference on Reanalysis in Rome:

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Introduction


Time slot Title Speaker (affiliation)

10.30–11.30am ICR5 Media Briefing

1pm Start of the Conference

1–1.15pm W.01 Welcome/Opening Roberto Buizza (ECMWF) and Paul Poli (Météo-France)

1.15–1.30pm W.02 Address from Copernicus Jean-Noel Thépaut (C3S-ECMWF) and Hugo Zunker (EC DG GROW

1.30–1.45pm W.03 Address from WMO/WCRP Deon Terblanche (WMO)

1.45–2pm W.04 Address from Italian Rep to WMO Silvio Cau (Director, Italian Meteorological Service)

2–2.30pm Invited Keynote K.1 Reanalysis: Past, Present, and Future

Adrian Simmons (ECMWF)

2.30–6pm Section 1 – Status and plans of reanalysis productions Chairs: Michael Bosilovich (NASA GMAO), Shinya Kobayashi (JMA), Simona Masina (CMCC)

2.30–3pm Invited Talk R.01 On the Significance of Using High- Resolution Sea-Surface Temperature in Atmospheric Reanalysis Production

Hisashi Nakamura (University of Tokyo)

3–3.45pm Group photo and coffee break


3.45–4pm R.02 State-of-the-art Atmospheric Reanalysis at ECMWF

Hans Hersbach (ECMWF)

4–4.15pm R.03 Earth System Data Assimilation and Reanalysis Efforts Supported by the NOAA Climate Program Office’s MAPP Program

Annarita Mariotti (NOAA)

4.15–4.30pm R.04 Status and plans for reanalysis at the NASA Global Modeling and Assimilation Office

Ron Gelaro (NASA GMAO)

4.30–4.45pm R.05 Reanalysis at the Japan Meteorological Agency

Shinya Kobayashi (JMA)

4.45–5pm R.06 Improvements in the Twentieth Century Reanalysis Version 3

Laura Slivinski (CU/CIRES & NOAA)

5–5.15pm R.07 CMA Global Reanalysis: Status and Plans

Ziquan Liu (CMA and NCAR)

5.15–5.30pm R.08 The CMEMS global and regional ocean reanalyses: towards a consistent set of high resolution ocean reanalyses for operational oceanography users and ocean state monitoring

Marie Drevillon (Mercator Océan)

5.30–5.45pm R.09 The CMCC Global Ocean Reanalysis System (C- GLORS): a multi-purpose family of eddy-permitting ocean reanalyses

Andrea Storto (CMCC)

5.45–6pm R.10 CERA-SAT: coupled reanalysis in the satellite-era

Dinand Schepers (ECMWF)

6–7.30pm Ice-breaker (drinks and finger food)

Monday 13 November



9–9.45am Invited Keynote K.2 Future Earth-System reanalyses: A land perspective

Sonia Seneviratne (ETH Zürich)

9.45–11.15am Section 1 (continued) – Status and plans of reanalysis productions Chairs: Michael Bosilovich (NASA GMAO), Shinya Kobayashi (JMA), Simona Masina (CMCC)

9.45–10am R.11 Improving the representation of the Greater Arctic with ASRv2

David Bromwich (Ohio State University)

10–10.15am R.12 BARRA: a high-resolution Atmospheric Reanalysis for 1990-2016 over Australia

Chun-Hsu Su (Australia Bureau of Meteorology)

10.15–10.30am R.13 PRECISE – Production of a regional Reanalysis for Europe within the Copernicus Climate Change Services

Semjon Schimanke (Swedish Meteorological and Hydrological Institute)

10.30–11.15am Coffee break


11.15–11.30am R.14 Reanalyses of Atmospheric Composition at ECMWF: from MACC to CAMS

Antje Inness (ECMWF)

11.30am–12.15pm Section 2 – Observations for reanalyses Chairs: Stefan Brönnimann (University of Bern), Nick Rayner (Met Office)

11.30am-12pm O.01 (Invited Talk) Preparing ocean observations for reanalysis

Nick Rayner (Met Office)

12–12.15pm O.02 Data rescue activities to support reanalysis and climate services: the EU-funded UERRA and EURO4M projects approaches and outcomes

Manola Brunet (Universitat Rovira i Virgili, Tarragona)

12.15–12.30pm Introduction to Poster Session # 1

12.30–2pm Lunch and Poster Session # 1 Posters on Status and plans of reanalysis productions, Observations for reanalyses, and Methods for reanalyses with authors standing in front of poster from 1pm to 2pm

Tuesday 14 November



2–3.45pm Section 2 (continued) – Observations for reanalyses Chairs: Stefan Brönnimann (University of Bern), Nick Rayner (Met Office)

2–2.15pm O.03 Data Recovery Effort of Nimbus era Observations by the NASA GES DISC

James Johnson (NASA/GSFC)

2.15–2.30pm O.04 Homogenized radiosonde temperature data for climate reanalyses

Leopold Haimberger (University of Vienna)

2.30–2.45pm O.05 The Copernicus Climate Change Service Global Land and Marine Observations Database: Plans and progress to date

Peter Thorne (Maynooth University)

2.45–3pm O.06 The benefits for reanalysis of reprocessing the surface marine climate record

Elizabeth Kent (National Oceanography Centre)


3–3.15pm O.07 EUMETSAT Data Records in Support of Reanalysis

Jörg Schulz (EUMETSAT)

3.15–3.30pm O.08 A Fundamental Climate Data Record of SSM/I, SSMIS, and SMMR brightness temperatures

Karsten Fennig (DWD)

3.30-3.45pm O.09 Observing Mass Variability in the Earth System with the Satellite Gravity Missions GRACE and GRACE-FO

Henryk Dobslaw (GFZ Potsdam)

3.45-4.30pm Coffee break

4.30–6pm Panel discussion – Reanalysis: from research challenges to operational applications and services

Moderator: Deon Terblanche, Acting Director, WCRP

Tuesday 14 November continued



9am–12.15pm Section 3 – Methods for reanalyses Chairs: Magdalena Alonso-Balmaseda (ECMWF), Gil Compo (CU/CIRES & NOAA), Dick Dee (C3S), Zhiquan Liu (NCAR & CMA)

9–9.30am M.01 (Invited Talk) Dynamically and kinematically consistent global ocean state and parameter estimation in support of climate research

Patrick Heimbach (University of Texas at Austin)

9.30–9.45am M.02 Uncertainty estimation in modern reanalysis systems

András Horányi (ECMWF)

9.45–10am M.03 Impact of Optimal Assimilation Windows in Coupled Data Assimilation on AMOC Analysis

Shaoqing Zhang (Ocean University of China)

10–10.15am M.04 The ECMWF weak-constraint 4D-Var formulation and a comparison between 12 and 24 hour assimilation window length to produce recommendations for future reanalysis as part of the ERACLIM2 project

Jacky Goddard (ECMWF)

10.15–10.30am M.05 Using hybrid data assimilation for reanalyses

Amal El Akkraoui (NASA GMAO)



11.15–11.30am M.06 A Method for Snow Reanalysis: The Sierra Nevada (USA)

Manuela Girotto (NASA/GSFC)

11.30–11.45am M.07 Atmospheric reanalysis for multi centuries using historical weather archives and isotopic proxies

Kei Yoshimura (University of Tokyo)

11.45am–12pm M.08 Paleoclimate reanalyses as a tool to understand the signal recorded by observations over the past millennium

Hugues Goosse, (Université de Louvain)

12–12.15pm M.09 A global climate reconstruction using data assimilation

Stefan Brönnimann (University of Bern)


12.30–2pm Lunch and Poster Session # 2 Posters on Evaluation and intercomparisons of reanalyses with authors standing in front of poster from 1pm to 2pm

2–2.30pm Section 3 (continued) – Methods for reanalyses Chairs: Magdalena Alonso-Balmaseda (ECMWF), Gil Compo (CU/CIRES & NOAA), Dick Dee (C3S), Zhiquan Liu (NCAR & CMA)

2–2.15pm M.10 Reanalysis in the Whole Atmosphere Models: From Nudging Techniques to Data Analysis in the Mesosphere and Lower Thermosphere

Valery Yudin (CU/CIRES & NOAA)

Wednesday 15 November



2.15–2.30pm M.11 Earth system climate reanalyses at ECMWF

Patrick Laloyaux (ECMWF)

2.30–5pm Section 4 – Evaluation and intercomparisons of reanalyses Chairs: Franco Desiato (ISPRA), Masatomo Fujiwara (Hokkaido University), Sonia Seneviratne (ETH), Adrian Simmons (ECMWF)

2.30–3pm E.01 (Invited Talk) Results from the SPARC Reanalysis Intercomparison Project (S-RIP) during 2013-2017

Masatomo Fujiwara (Hokkaido University)

3–3.15pm E.02 Assessment of upper tropospheric and stratospheric water vapor and ozone in reanalyses as part of S-RIP

Sean Davis (NOAA ESRL)

3.15–3.30pm E.03 Preliminary assessment of the ERA5 ozone reanalyses

Rossana Dragani (ECMWF)

3.30–4.15pm Coffee break


4.15–4.30pm E.04 Mean age of stratospheric air since 1985: large disagreements between five modern reanalyses

Simon Chabrillat (BIRA-IASB)

4.30–4.45pm E.06 Towards consistent diagnostics of the coupled atmosphere and ocean energy budgets

Michael Mayer (University of Vienna)

4.45–5pm E.07 Land surface precipitation and hydrology in MERRA-2

Rolf Reichle (NASA/GSFC)

5-5.45pm Invited Keynote K.3 Future Earth-System reanalyses: An atmospheric perspective

Gil Compo (CU/CIRES & NOAA)

Wednesday 15 November continued



9–11.45am Section 4 (continued) – Evaluation and intercomparisons of reanalyses Chairs: Franco Desiato (ISPRA), Masatomo Fujiwara (Hokkaido University), Sonia Seneviratne (ETH), Adrian Simmons (ECMWF)

9–9.15am E.08 Quantifying spatio-temporal variations of soil moisture control on surface energy balance and near- surface air temperature

Clemens Schwingshackl (ETH)

9.15–9.30am E.09 Assessment of precipitation in the CERA-20C and ERA-20C reanalyses by means of precipitation gauge observations

Elke Rustemeier (DWD)

9.30-9.45am E.10 Improved SST-precipitation relationships in the CERA-20C coupled climate reanalysis

Xiangbo Feng (University of Reading)

9.45–10am E.11 An intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses from the project ORA-IP

Matthieu Chevallier (Météo- France)

10–10.15am E.12 Uncertainty in Reanalysis over Europe Peter Jermey (Met Office)

10.15–10.30am E.13 800+ site validation of Reanalysis & downscaled wind conditions time series

Gil Lizcano (Vortex)



11.15–11.30am E.14 Do reanalyses capture long-term changes in extreme weather statistics?

Prashant Sardeshmukh (CU/CIRES & NOAA)

11.30–11.45am E.15 AFES-LETKF data assimilation system for an experimental atmospheric global ensemble reanalysis

Akira Yamazaki (JAMSTEC)

11.45am–12.15pm Section 5 – Applications of reanalyses Chairs: Andrea Kaiser-Weiss (DWD), Carolin Richter (WMO), Michel Rixen (WCRP), Jean-Noël Thépaut (C3S-ECMWF)

11.45am–12.15pm Invited Talk A.01 Insights into the role of the oceans in the Earth energy budget from ocean reanalysis

Karina Von Schuckmann (Mercator)


12.30–2pm Lunch and Poster Session # 3 Posters on Applications of reanalyses with authors standing in front of poster from 1pm to 2pm

Thursday 16 November



2–5pm Section 5 (continued) – Applications of reanalyses Chairs: Andrea Kaiser-Weiss (DWD), Carolin Richter (WMO), Michel Rixen (WCRP), Jean-Noël Thépaut (C3S-ECMWF)

2–2.15pm A.02 Reanalyses’ use in operational weather forecasting

Roberto Buizza (ECMWF)

2.15–2.30pm A.03 Stratospheric intrusion-influenced ozone air quality exceedances investigated in the NASA MERRA-2 Reanalysis

Katherine Emma Knowland (NASA GMAO)

2.30–2.45pm A.04 Classification of Meteorological Influences Surrounding Extreme Precipitation Events in the United States using the MERRA-2 Reanalysis

Allison Collow (NASA/GSFC)

2.45–3pm A.05 Role of Southern Annular Mode on Asian Monsoon: Mechanisms through NCEP-NCAR Reanalysis

Amita Prabhu (Indian Institute of Tropical Meteorology)

3–3.15pm A.07 Intercomparison of the near-surface wind speed trends in three reanalyses

Verónica Torralba (Barcelona Supercomputing Center)


3.15–3.30pm A.08 On requirements for the application of reanalyses in the context of climate monitoring and energy applications in Germany

Frank Kaspar (DWD)

3.30–4.15pm Coffee break

4.15–4.30pm A.09 On the use of the 50-year high-resolution UERRA re-analysis for a hydro-meteorological application over Europe

Patrick Le Moigne (Météo-France)

4.30–4.45pm A.10 Development of long-term hydro-meteorological reconstructions over France based on large scale atmospheric reanalyses to study the multi-decadal variability of French river flows

Rémy Bonnet (CERFACS)

4.45–5pm A.11 From data mining to information extraction: using ERA-INTERIM reanalysis to model hydro-power production in Europe

Matteo De Felice (ENEA)

5–5.45pm Invited Keynote K.4 Future Earth-System reanalyses: An ocean perspective

Magdalena Alonso-Balmaseda (ECMWF)

Thursday 16 November continued



9–10.30am Section 5 (continued) – Applications of reanalyses Chairs: Andrea Kaiser-Weiss (DWD), Carolin Richter (WMO), Michel Rixen (WCRP), Jean-Noël Thépaut (C3S-ECMWF)

9–9.15am A.12 Mediterranean Sea circulation in high-resolution hindcast simulations and reanalyses

Gianmaria Sannino (ENEA)

9.15–9.30am A.13 A three-dimensional characterisation of eddy activities in a global ocean eddy-permitting reanalysis

Andrea Cipollone (CMCC)

9.30–9.45am A.14 Downscaling ERA5 reanalysis data for coastal climate applications and evaluation of uncertainty of coastal data

Carlo Brandini (CNR)

9.45–10am A.15 A roadmap to Earth surface kilometre-scale simulations

Gianpaolo Balsamo (ECMWF)

10–10.30am Coffee break

10.30am–12.30pm

Summary and key messages from the 5 Sections and Plenary discussion

10.30–10.45am S.01 Summary and key message from Section 1

Michael Bosilovich (NASA GMAO), Shinya Kobayashi (JMA), Simona Masina (CMCC)


10.45–11am S.02 Summary and key message from Section 2

Stefan Brönnimann (University of Bern), Nick Rayner (Met Office)


Magdalena Alonso-Balmaseda (ECMWF), Gil Compo (CU/CIRES & NOAA), Dick Dee (C3S), Zhiquan Liu (NCAR & CMA)


Franco Desiato (ISPRA), Masatomo Fujiwara (Hokkaido University), Sonia Seneviratne (ETH), Adrian Simmons (ECMWF)


Andrea Kaiser-Weiss (DWD), Carolin Richter (WMO), Michel Rixen (WCRP), Jean-Noël Thépaut (C3S-ECMWF)

11.45am–12.30pm

Plenary discussion Michel Rixen (WMO/WCRP), Roberto Buizza (ECMWF) and Paul Poli (Météo-France)

12.30-1pm Closure

Friday 17 November


Talks


KeynotesReanalysis: Past, Present and Future

Author Adrian Simmons

Affiliation ECMWF

The development of the observing system for weather and climate, and the origins, evolution, achievements and applications of reanalysis will be reviewed. Future directions will be indicated. Emphasis will be placed on some of the challenges that have been encountered in undertaking reanalysis, presenting examples of the significant progress that has been made and discussing issues, longer-standing and emerging, that remain to be satisfactorily addressed. Broader institutional matters, including international cooperation, will also be discussed.

Future Earth-System reanalyses: A land perspective

Author Sonia Seneviratne Affiliation ETH Zürich

Future Earth-System reanalyses: An atmospheric perspective

Author Gilbert P. Compo

Affiliation University of Colorado CIRES & NOAA, Earth System Research Laboratory, Physical Sciences Division

Co-authorsJ.S. Whitaker (NOAA Earth System Research Laboratory, Physical Sciences Division), P.D. Sardeshmukh (University of Colorado at Boulder, CIRES & NOAA Earth System Research Laboratory, Physical Sciences Division), L.C. Slivinski (University of Colorado at Boulder, CIRES & NOAA Earth System Research Laboratory, Physical Sciences Division), P. Brohan (Met Office Hadley Centre), and R. Allan (Met Office Hadley Centre)

Since 1819, when Brandes followed up on his original 1816 proposal for making a “weather map” by retrospectively analyzing the surface pressure over parts of Europe for every day of the year 1783, atmospheric “reanalysis” has been a staple of weather and climate science. In the 20th century, massive subjective reanalysis efforts of the early century were followed by the modern achievement of consistent data assimilation systems from numerical weather prediction being applied retrospectively to surface and upper-air

observations from the 1940s to the 1970s and then including satellite observations to today.

In the 21st century, these “full-input” reanalyses have advanced, and additional work has also generated reanalysis datasets using advanced data assimilation systems and only surface observations that extend reanalysis back to the 1850s. These accomplishments, though successful, have still left several areas of great societal relevance in need of attention. Among these, for the complete period of the instrumental record extending back to the 18th century, future reanalyses of the atmosphere need to achieve success in providing reliable representation of the climate and variability of extreme weather statistics; high impact weather phenomena, such as tropical cyclones; and atmospheric trace gases and aerosols.

All of these should be determined from the surface of the earth to the boundaries of space. Thoughts on the current status and possibilities for achieving these goals for datasets spanning the continually-evolving instrumental record back to Brandeis’s original reanalysis maps will be discussed.


Future of Earth System Reanalyses: An Ocean Perspective

Author Magdalena Alonso Balmaseda

Affiliation ECMWF

Ocean reanalyses capabilities have gone a long way during the last decade, fuelled by advances in the ocean observing system, model and data assimilation methods, availability atmospheric reanalyses, as well as concerted community efforts in production and inter-comparison.

Nowadays ocean reanalyses are produced routinely by a number of institutions to monitor the ocean climate and to initialize weather and climate predictions. As the field advances, so are expectations and the potential applications. The inherent quest for increasing quality (longer time span, increased resolution and temporal consistency, uncertainty estimates) goes hand in hand with new scientific questions and a wider range of demands.

In particular, reanalyses are now key for the understanding of the energy, water and carbon cycles. Consistent century-long reanalyses able to exploit the sparse observations in the distant past as well as the wealth of current high-resolution observations are also needed to initialize seasonal and decadal predictions. These primary challenges in our efforts to predict, mitigate and adapt to climate change. Coupled earth system reanalyses offer a path to tackle these critical questions.

They should provide traceable inventories of transports, sources and sinks, involved in the primary climate cycles, and, in principle, they are powerful tools to optimise the use of observations. But this is a major undertaking, paved with new challenges, which will require major development in assimilation methodology, coupled modelling and activities in data rescue.

Keynotes


(to be completed early 2018) covers, like ERA-Interim, the satellite period from 1979 onwards.

Monthly updates are provided and consolidated in an official release about two to three months behind real time, although preliminary data products will be made available within a week of production. In a second phase (production to start in 2018) a pre-extension back to 1950 is planned. ERA5 will provide a large number of essential climate variables within the C3S Climate Data Store (CDS).

Compared to ERA-Interim, ERA5 incorporates many important innovations that safeguard the provision of state-of-the-art climate reanalysis. ERA5 is based on a recent version of the ECMWF Integrated Forecast Model which includes numerous improvements to the 4D-Var assimilation method as well as the coupled atmosphere, ocean waves and land model.

State-of-the-art Atmospheric Reanalysis at ECMWF

Author Hans Hersbach

Affiliation ECMWF

Co-authorsPaul Berrisford (ECMWF), Gionata Biavati (ECMWF), Per Dahlgren (ECMWF), Dick Dee (ECMWF), Rossana Dragani (ECMWF), Manuel Fuentes (ECMWF), Andras Horanyi (ECMWF), Joaquin Munoz-Sabater (ECMWF), Carole Peubey (ECMWF), Raluca Radu (ECMWF), Iryna Rozum (ECMWF), Dinand Schepers (ECMWF), Adrian Simmons (ECMWF), Cornel Soci (ECMWF), Jean-Noël Thépaut (ECMWF) and Sebastien Villaume (ECMWF)

At the European Centre for Medium-Range Weather Forecasts (ECMWF), reanalysis is a key contribution to the Copernicus Climate Change Service (C3S) that is implemented at ECMWF on behalf of the European Commission. This presentation provides an overview of the latest ECMWF atmospheric reanalysis ERA5, which is currently in production and will replace the widely used ERA-Interim reanalysis.

ERA5 is the fifth generation of ECMWF atmospheric reanalyses of the global climate, which was pioneered with the FGGE reanalyses produced in the 1980s, followed by ERA-15, ERA-40 and most recently ERA-Interim. Production is taking place in two phases. A first phase

years. The other is an additional product (JRA-55CHS) with MGDSST data with a 25-km resolution only over 28 recent years.

The comparison reveals substantial differences in midlatitude atmospheric processes around the western boundary currents and associated SST fronts. As a typical example, atmospheric response to variability of the Kuroshio Extension (KE) is examined. As in satellite observations, enhancement of cloudiness and precipitation in the oceanic frontal zone east of Japan during the unstable regime of KE relative to its stable regime is represented well in JRA-55CHS but not in JRA-55C product. The enhancement, which results from augmented heat/moisture release from the warmer ocean with more active warm-core eddies, comes to be better represented in ERA-Interim after 2001, when the SST resolution was improved.

This oceanic thermal forcing onto the atmosphere is manifested as positive correlation in anomalies between SST and heat/moisture release, which is represented only in the high-resolution MGDSST but not in COBE SST. As another example, stormtrack response to meridional displacement of the Oyashio front is examined. Again, the positive correlation between anomalous SST and heat/moisture release is much stronger in JRA-55CHS, and so is the enhancement of convective precipitation over warm SST anomalies.

Section 1 – Status and plans of reanalysis products

On the Significance of Using High-Resolution Sea-Surface Temperature in Atmospheric Reanalysis Production

Author Hisashi Nakamura

Affiliation University of Tokyo

Co-authorsR. Masunaga (Univ. Tokyo), H. Kamahori (MRI-JMA), C. Kobayashi (MRI-JMA), S. Okajima (Univ. Tokyo), T. Miyasaka (Univ. Tokyo), K. Nishii (Mie Univ.)

Recent studies have identified distinct impacts of the warm western boundary currents, such as the Gulf Stream and Kuroshio, and associated midlatitude frontal zones on the overlying atmosphere, including boundary-layer wind/thermal structure, vertical motion and cloud-precipitation systems.

Their representation in reanalysis should be sensitive to the resolution of SST data prescribed at the lower boundary of a forecast model, and the sensitivity is assessed through comparison of two products of a new Japanese reanalysis (JRA-55). One is JRA-55C, in which observed data have been assimilated in a forecast system with horizontal resolution of ~60km and the COBE SST data with 1-deg. resolution prescribed over 55


and aerosol observations as a weakly coupled assimilation system as a first step toward GMAO’s longer term goal of developing an integrated Earth system analysis (IESA) capability that will couple assimilation systems for the atmosphere, ocean, land and chemistry.

The GMAO strategy is to progress incrementally toward an IESA through an evolving combination of coupled systems and offline component reanalyses driven by, for example, MERRA-2 atmospheric forcing. Most recently, the GMAO has implemented a weakly coupled assimilation scheme for analyzing ocean skin temperature within the existing atmospheric analysis.

The scheme uses background fields from a near-surface ocean diurnal layer model to assimilate surface-sensitive radiances plus in-situ observations along with all other observations in the atmospheric assimilation system. In addition, MERRA-2-driven simulations of the ocean (plus sea ice) and atmospheric chemistry (for the EOS period) are currently underway, as is the development of a coupled atmosphere-ocean assimilation system.

This talk will describe the status of these ongoing efforts and the planned steps toward an IESA capability for climate research.

product at an enhanced resolution. The presentation will conclude with an outlook on plans for the next ECMWF C3S reanalysis, ERA6.

Status and plans for reanalysis at the NASA Global Modeling and Assimilation Office

Author Ron Gelaro

Affiliation NASA, Goddard Space Flight Center (GSFC), Global Modeling and Assimilation Office (GMAO)

Co-authorsS. Pawson (1), A. da Silva (1), W. Putman (1), W. McCarty (1), A. El Akkraoui (2,1), S. Akella (2,1) 1: NASA Goddard Space Flight Center, Greenbelt, MD, USA, 2: Science Systems and Applications, Inc., Lanham, MD, USA

Reanalysis plays a critical role in GMAO’s goal to enhance NASA’s program of Earth observations, providing vital data sets for climate research and the development of future missions. As the breadth of NASA’s observations expands to include multiple components of the Earth system, so does the need to assimilate observations from currently uncoupled components of the system in a more physically consistent manner.

GMAO’s most recent reanalysis of the satellite era, MERRA-2, has completed the period 1980-present, and is now running as a continuing global climate analysis with two- to three-week latency. MERRA-2 assimilates meteorological

key research priorities. This presentation will discuss various activities of the MAPP Program to advance Earth system DA and reanalysis.

Radiative forcing data are used that represent the observed evolution of greenhouse gases, volcanic eruptions, ozone and aerosols, and consistent boundary conditions are used for sea-surface temperature and sea ice. A number of reprocessed data records are ingested as well as several data sets that have never before been used in reanalysis. ERA5 is able to assimilate data from the latest instruments. Observation bias correction schemes have been extended and improved.

ERA5 is produced at considerably higher resolution than ERA-interim: hourly analysis fields are available at a horizontal resolution of 31 km on 137 levels in the vertical. Data products include information about uncertainties generated by a lower-resolution (62 km) 10-member 4D-Var ensemble. A number of new parameters, such as 100-metre wind speed and direction, are available as part of the output, based on user requirements and identified gaps in previous reanalysis productions.

A database containing all ingested observations, together with detailed information about how they are used, is available to users. In addition, a dedicated ERA5 land component will deliver a land-surface reanalysis

Earth System Data Assimilation and Reanalysis Efforts Supported by the NOAA Climate Program Office’s MAPP Program

Author Annarita Mariotti

Affiliation NOAA Climate Program Office – MAPP Program

Co-authorsH. Archambault, and D. Barrie (NOAA Climate Program Office – Modeling, Analysis, Predictions, and Projections) Program

The Modeling, Analysis, Predictions, and Projections (MAPP) Program is a competitive grants program in the NOAA Office of Oceanic and Atmospheric Research Climate Program Office that supports data assimilation (DA) and new techniques for reanalysis as part of its core mission.

Recently, the MAPP Program funded a set of projects to evaluate and improve aspects of NOAA’s reanalysis for climate monitoring and prediction, with the investigators leading these projects constituting the MAPP Climate Reanalysis Task Force.

Now, as NOAA moves toward a unified modeling and DA framework to support monitoring and prediction of the Earth system across timescales, the MAPP Program has identified coupled DA and improved or new DA-based monitoring products for the ocean, cryosphere, land surface, and atmospheric composition as

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Additionally, the algorithms needed to represent sampling and model error, covariance inflation and localization, have been updated in version 3 and have led to improved quantification of uncertainty. Results with the previous system (version 2c) show that the uncertainty tends to be too low in data-rich regions, and too high in data-sparse regions; these effects are generally improved upon in the version 3 system. The new version also includes a bias correction to marine observations prior to 1870, which is calculated offline and considers the particular ship from which the observation came. Results of testing this new bias correction and other improvements will be discussed.

CMA Global Reanalysis: Status and Plan

Author Zhiquan Liu

Affiliation NCAR & China Meteorological Administration (CMA)

Co-authorsLipeng Jiang, Tao Zhang, Jie Liao, Chunxiang Shi, Zijiang Zhou, Lijuan Cao, Kaixi Hu, Hui Jiang, Xiao Liang, Jingwei Liu, Dong Si, Chenghu Sun, Mingyan Wang, Shuang Yao, Yizhou Yin, Zhishen Zhang, Bin Zhao (CMA)

CMA started a global reanalysis effort from early 2014, which aims to producing 40 years (1979-2018) atmospheric and land reanalysis products (CRA-40) by 2020 and then continuing it as the operational climate analysis system for climate monitoring and service purposes.

Improvements in the Twentieth Century Reanalysis Version 3

Author Laura C. Slivinski

Affiliation Univ. of Colorado’s Cooperative Institute for Research in Environmental Sciences

Co-authorsG.P. Compo (CIRES/NOAA), J.S. Whitaker (NOAA), P.D. Sardeshmukh (CIRES/NOAA)

The international Twentieth Century Reanalysis (20CR) project led by NOAA and CIRES provides global, subdaily weather estimates throughout the troposphere stretching back over 150 years. It assimilates only surface pressure observations into the NCEP Global Forecast System constrained by sea surface temperatures and sea ice concentration. In addition, the ensemble Kalman filter data assimilation method used in 20CR provides quantification of uncertainty around these estimates via the ensemble spread.

The new version 3 system incorporates several improvements over the previous data set, version 2c, including a higher-resolution model, a larger ensemble, and more observations. Version 3 uses a more sophisticated data assimilation algorithm than version 2c, leading to a reduction of spurious trends in 6-hour precipitation forecasts from version 2c.

of temperature analysis is, in particular, improved considerably over that of previous reanalyses. For variables and regions in which the forecast model has large biases, however, there still remain large uncertainties in the represented trends due to the fact that degree of constraint on the model biases varies with changes in observing systems. The upper and middle tropospheric humidity, for example, shows spurious trends due to the fact that a dry bias tends to diminish slightly as the number of observations from satellite water vapour channels increases.

To facilitate investigations on the credibility of low-frequency variability and trends represented in JRA-55, the JMA Meteorological Research Institute has produced a reanalysis assimilating conventional observations only, called JRA-55C, and an AMIP-type simulation, called JRA-55AMIP.

These are produced with the same numerical weather prediction system as used for JRA-55, and they are made available together with JRA-55 products as the JRA-55 family. JMA is currently preparing the next reanalysis, called the Japanese Reanalysis for Three Quarters of a Century (JRA-3Q), with the aim of producing a more improved reanalysis and contributing to climate services and climate research.

Reanalysis at the Japan Meteorological Agency

Author Shinya Kobayashi

Affiliation Japan Meteorological Agency

One of the major issues in reanalysis is temporal consistency extending over decadal and longer time scales. Improving temporal consistency in future reanalyses is essential for improving operational climate services and advancement in climate research. For this end, the Japan Meteorological Agency (JMA) conducted the Japanese 55-year Reanalysis (JRA-55) for the period from 1958 onward. JRA-55 has been produced with the TL319 version of JMA’s operational data assimilation system as of December 2009, and its production has been continued on a near-real-time basis.

This system features numerous improvements made since the previous Japanese reanalysis (JRA-25). JRA-55 also incorporates several newly available observational datasets produced as a result of ongoing efforts to improve quality of past observations, including homogenization of radiosonde temperature observations and reprocessing of satellite data at major meteorological satellite centres.

These improvements have made JRA-55 products considerably better than JRA-25 products; the temporal consistency

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The CMCC Global Ocean Reanalysis System (C-GLORS): a multi-purpose family of eddy-permitting ocean reanalyses

Author Andrea Storto

Affiliation CMCC

Co-authorsS. Masina (CMCC and INGV), A. Cipollone, D. Iovino (CMCC)

An eddy-permitting global ocean reanalysis system is under continuous development at CMCC. The system is called C-GLORS (CMCC Global ocean reanalysis system) and implements a 3DVAR data assimilation scheme to assimilate hydrographic profiles and altimetry data, a nudging scheme for assimilating sea-surface temperature and sea-ice concentration data from satellite, and a large-scale bias correction scheme.

The ocean model component is NEMO at 1/4 degree resolution coupled with the LIM2 sea-ice thermo-dynamical and dynamical model. Here we present an historical perspective on the CMCC ocean reanalysis activities during the last decade, focusing on the main achievements reached, from past coarse-resolution retrospective analyses to the recent real-time ensemble ocean reanalyses used for initializing the CMCC seasonal prediction system, to the latest release included in the Copernicus Marine Service catalogue

These developments must rely on continuous and high quality reanalyses and reprocessing time series, which go up to real time. Both C3S and CMEMS reanalyses are used.

The CMEMS reanalyses are different and complementary to the C3S reanalyses, which first objective is to achieve the accurate description of climate variability. CMEMS reanalyses aim at a seamless connection with CMEMS real time analyses and forecast, thus CMEMS regional reanalyses particularly benefit from both higher resolution and specific regional tunings.

Particular efforts are put on the processing of sea ice and biogeochemistry components. CMEMS assures the collections of “best quality” input data and maximal use of multiple observation systems, and, on the long term, aims at a fully consistent approach across global and regional reanalyses, organizing their interoperability, their inter-dependencies, and joint operations closer to real time (a few months only) with a systematic yearly update.

The CMEMS global and regional ocean reanalyses: towards a consistent set of high resolution ocean reanalyses for operational oceanography users and ocean state monitoring

Author Marie Drévillon

Affiliation Mercator Océan

Co-authorsK. von Schuckmann (Mercator Océan) P.-Y. Le Traon (Mercator Océan, Ifremer)

The Copernicus Marine Environment Monitoring Service CMEMS aims to deliver generic and reliable information, derived from space and in-situ observations and from models – including forecasts, analyses and reanalyses – on the physical and biogeochemical state over the global ocean and the European regional seas. One of the main requirements from operational oceanography users is to have long time series of data as a reference statistical and quality framework.

Among those users, environmental agencies also require ocean state and marine environment monitoring, which is achieved through the annual release of the CMEMS Ocean State Report (OSR) to monitor and describe ocean variability and change from the past to present; and through the development of operational Ocean Monitoring Indicators (OMIs), and related error bars.

The original plan was to produce CRA-40 by upgrading CMA’s operational NWP system of 2014. However, experimental tests in 2015 showed that the operational system could not produce reanalysis products with desired quality.

After further testing and comparison, it is decided in late 2016 that this first generation CMA reanalysis will move to NOAA’s GFS/GSI-based model and data assimilation system for atmospheric component and recently released NASA’s Land Information System (LIS) for land component. Thus far, more than 100 TB historical conventional and satellite observations were collected. Some careful data evaluation and quality control were performed with emphasis on better usage of data from Chinese observing networks.

Currently, a 10-year (2007/01-2016/12) Interim reanalysis is in production with GFS and GSI-3DVAR at T574 spectral resolution and shall be completed this September. Preliminary evaluation of this CRA-Interim product and future plan will be presented.

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for a comprehensive integration of the regional climate of the Arctic for 2000-2012.

ASRv2 surface and pressure level products are available at 3-hourly and monthly-mean timescales at NCAR. ASRv2 has new features including higher resolution depiction in space (15 km horizontal resolution), updated model physics including sub-grid scale cloud fraction interaction with radiation, and a dual outer loop routine for more accurate data assimilation.

An evaluation of ASRv2 yields a superior reproduction of near-surface and tropospheric variables. Forecast precipitation and downward radiative fluxes demonstrate significant improvement over ASRv1. The high-resolution topography and land surface, including weekly-updated vegetation and realistic sea-ice fraction, thickness, and snow cover depth resolve fine-scale processes such as topographically-forced winds.

Thus, ASRv2 is particularly suitable for detailed investigations of near-surface characteristics during the period of rapid Arctic change; and therefore, complements the multi-decadal perspective of the global reanalyses.

Improving the representation of the Greater Arctic with ASRv2

Author David H. Bromwich

Affiliation Ohio State University

Co-authorsA.B. Wilson (1), L-S Bai (1), Z. Liu (2), M. Barlage (2), C-F Shih (2), S Maldanado (1), K.M. Hines (1), S-H Wang (1), J. Woollen (3), B. Kuo (2), H-C Lin (2), T-K Wee (2), M.C. Serreze (4), and J.E. Walsh (5). 1: Ohio State University, 2: NCAR, 3: NOAA NCEP, 4: University of Colorado-Boulder, 5: University of Alaska-Fairbanks.

The Arctic is in the midst of rapid environmental changes, spurred by amplified effects due to human activities and natural variability. Global atmospheric reanalyses that merge a wide variety of surface, atmospheric and satellite remote sensing data into gridded analyses have long been relied upon to investigate Arctic climate change and accompanying variability during recent decades. However, changing observing systems create issues for climate change investigations.

This presentation introduces version 2 of the Arctic System Reanalysis (ASRv2), a multi-agency, university-led retrospective analysis (reanalysis) of the Greater Arctic (poleward of 45°N). ASRv2 uses blends of the polar-optimized version of the Weather Research and Forecasting (Polar WRF) model and WRF three-dimensional variational data assimilated observations

Earth System approach. It comprises coupled assimilation of atmosphere, ocean, waves, sea ice and land surface observations provided by the modern-day observing system.

At its heart sits a pioneering coupled ocean-atmosphere data assimilation system (CERA) which couples a 3D-Var ocean assimilation system (NEMOVAR) to the ECMWF Integrated Forecast System (IFS) 4D-Var atmospheric assimilation system at the outer loop level.

Weakly coupled to this is a land surface analysis based on a combination of optimal interpolation (OI) and simplified Extended Kalman Filter (EKF). CERA-SAT – projected to cover 8 years starting in 2008- is produced using a 10-member Ensemble of Data Assimilations (EDA) system coupling an atmosphere at 60 kilometre resolution on 137 vertical levels with an eddy-permitting quarter degree ocean model.

In this presentation we present the CERA-SAT coupled assimilation approach, features of the reanalysis data set and a preliminary assessment of benefits of coupled data assimilation in the data-rich satellite-era.

and the participation to international inter-comparison activities. Applications of the reanalysis and process-oriented analyses will be given as well, looking for instance at the effect of data assimilation on polar regions transports and eddy population, along with a detailed quality assessment. Finally, future directions including feasibility of updating the system to hybrid ensemble/variational four-dimensional data assimilation and plans for eddy-resolving reanalyses will be given.

CERA SAT: coupled reanalysis in the satellite-era

Author Dinand Schepers

Affiliation ECMWF

Co-authorsEric de Boisseson (ECMWF), Roberto Buizza (ECMWF), Per Dahlgren (ECMWF), Dick Dee (ECMWF), Yuki Kosaka (ECMWF, JMA), Patrick Laloyaux (ECMWF)

The European Centre for Medium-Range Weather Forecasts (ECMWF) is a key player in the production of reanalyses for climate monitoring as well as research. In line with the Earth system approach defined in the current ten year strategy, ECMWF has developed a coupled assimilation system for ingesting observations of ocean and atmosphere in a coupled ocean-atmosphere model.

CERA-SAT is a pilot reanalysis of the satellite-era -funded by the ERA-CLIM2 FP7 project- aimed at progressing the

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In this presentation, we will give an overview on what can be expected from the service within the next years. In the first phase, PRECISE products will be based on the model system developed in the pre-operational project UERRA (there will be separate presentations on UERRA, e.g. Ridal et al. and Undén et. al.). While UERRA produced data sets for the period 1961-2015, PRECISE will fill the gap throughout 2016 and early 2017.

This will be followed by monthly updates in near real-time. Hence, PRECISE will offer a consistent RRA from 1961 to near real time. The onset of the operational monthly updates can be expected in early 2018. All data will be saved with hourly resolution and will be freely available via the Copernicus Data Store (CDS). The production system will be discussed in the presentation. Here, we will focus on the challenges of producing the RRA operational in near real-time. In the second phase, it is planned to switch to a more advanced system that will be developed while the operational production of the RRA carries on during phase one.

The new PRECISE reanalysis system will be built on but extending from the UERRA system in several ways: The horizontal resolution of the data assimilation system will be enhanced from 11 km to 5.5 km and also the vertical resolution will be increased from 65 to about 90 levels. The top of the model will be raised to allow assimilation

such as surface winds and temperatures available every 10 minutes. Other output variables include moisture, pressure, cloud cover, precipitation, evaporation, energy fluxes, and soil water. Here we report on the implementation of BARRA and preliminary evaluations, and describe a range of its applications of immediate interest to meteorologists, fire and landscape managers, and other members of the emergency management community. This includes the use of reanalysis to create tailored fire weather products for the fire agencies.

PRECISE – Production of a regional Reanalysis for Europe within the Copernicus Climate Change Services

Author Semjon Schimanke

Affiliation SMHI

Co-authorsP. Undén (SMHI), M. Ridal (SMHI), L. Berggren (SMHI), P. Le Moigne (Météo-France), E. Bazile (Météo-France), H. Schyberg (MET Norway), R. Randriamampianina (MET Norway)

PRECISE (Production of a regional Reanalysis for Europe within the Copernicus Climate Change Services) is a Copernicus service that will be launched under summer 2017. The goal of the service is to provide a regional reanalysis (RRA) for the atmosphere over Europe, which will be updated in near real-time.

dry grass and high oil content in native plants. More broadly, benefits from the reanalysis are expected for land-use and water management, primary industries, and the health, energy, defence, and minerals sectors.

To fully realise benefits, researchers, governmental agencies and industry are collaborating to add value to the reanalysis data. BARRA is a 12-km regional-scale reanalysis, nested within the required boundary and/or initial conditions provided by the coarse-scale ERA-Interim reanalysis, Operational SST and Sea Ice Analysis, and the Bureau’s offline soil moisture reanalysis. We use an unchanging atmospheric modelling suite based on the UERRA (Uncertainties in Ensembles of Regional ReAnalysis) system used at the UK Met Office and the more recent version of the Unified Model used in the Bureau’s weather prediction systems.

A 4D deterministic variational data assimilation scheme is used to optimally combine model physics with multiple observations from aircraft, sondes, surface observations and satellites. BARRA also consists of multiple convective-scale (1.5 km) downscaling analyses driven by the 12 km system, for supporting fire services. Downscaling can be performed anywhere in the regional domain.

The temporal resolution of the output analysis fields for both the regional and higher-resolution subdomains are generally one hour, with many fields

BARRA: a high-resolution Atmospheric Reanalysis for 1990-2016 over Australia

Author Chun-Hsu Su

Affiliation Bureau of Meteorology

Co-authorsN. Eizenberg (Bureau of Meteorology, Docklands, Australia), G. Kociuba (Bureau of Meteorology, Docklands, Australia), P. Steinle (Bureau of Meteorology, Docklands, Australia), Dörte Jakob (Bureau of Meteorology, Docklands, Australia), Paul Fox-Hughes (Bureau of Meteorology, Hobart, Australia)

The Australian Bureau of Meteorology has commenced a project to produce a high-resolution 1990–2016 reanalysis covering the Australian continent and the surrounding regions, including New Zealand and parts of southeast Asia. This reanalysis is in the following referred to as BARRA (Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia). Production runs commenced in March 2017.

Jointly funded by fire and emergency service agencies in New South Wales, Tasmania, Western Australia and South Australia and with major co-contribution by the Bureau of Meteorology, this project supports high-quality assessments of risk and likelihood of wildfires, in Australia known as bushfires. These are frequent events during the warmer months of the year, owing to the Australian climate, vast areas of

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the last decade. ECMWF hasproduced several reanalyses of atmospheric composition (e.g. reactivegases, aerosols and greenhouse gases) under the EU funded GEMS and MACCprojects and the Copernicus Atmosphere Monitoring Service (CAMS).

These reanalyses use data assimilation to combine satellite retrievals of atmospheric composition with state of the art atmospheric composition models to produce long, consistent datasets. In this talk we will show results from the recent CAMS interimreanalysis which covers the period from 2003 to the present day andprovides analysis fields for CO, O3 and AOD. This reanalysis can, forexample, be used to evaluate recent trends (2003-2016) in CO, which aremainly caused by El-Nino (2015) and land-use induced changes in biomassburning as well as trends in anthropogenic emissions.

We will also showresults from the latest CAMS reanalysis which is being produced at themoment. Both reanalyses are based on a fully integrated approach combining both meteorology and atmospheric composition in one data assimilation system with the new CAMS reanalysis being more comprehensive, including many chemical species, aerosols and greenhouse gases.

The new reanalysis also exploits various interactions, such as the interaction between aerosol and radiation and the interaction between the meteorology and the land biosphere model for CO2.

of satellite radiances. Moreover, the number of layers in the boundary layer will increase.

The MESCAN surface analysis of temperature and humidity will be integrated in the production reanalysis since no downscaling will be necessary. New input data sets will be tried and integrated and a number of new observation types or instruments will be tested. The lateral boundary will be forced by the global ERA5 RA.

The onset of the production with the new system ushers the second phase of the service in, which is scheduled for 2019. The RRA dataset will start in the early 1980’s and will be updated operational in near real-time. Details of the advanced system as well as the time schedule will be discussed.

Reanalyses of Atmospheric Composition at ECMWF: from MACC to CAMS

Author Antje Inness

Affiliation ECMWF

Co-authorsJ. Flemming (ECMWF), R. Engelen (ECMWF), M. Ades (ECMWF), A Agusti-Panareda (ECMWF), Z. Kipling (ECMWF), S. Massart (ECMWF), M. Parrington (ECMWF), M. Suttie (ECMWF), V-H. Peuch (ECMWF)

In addition to meteorological reanalyses, reanalysis data sets ofatmospheric composition have been emerging in

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the DARE effort includes meteorological stations in western and eastern Mediterranean, North Africa, the Middle East, the Balkans, central and eastern Europe and Scandinavia mostly for the post-1950 period.

The targeted variables have been air pressure, air temperature, dew-point, relative humidity, cloud cover and wind speed and wind direction (precipitation, snow-depth, fresh snow) at the hourly (daily and sub-daily) scales.

ASRv2 products may be used to force other environmental models, verify regional processes, or aid in the siting of future observation networks.

2017) focus is on producing ensembles of regional reanalyses for several decades and estimating the associated uncertainties in the derived data sets. Both projects have a core component of data rescue (DARE) of meteorological observations, while ensuring DARE coordination to avoid duplicating efforts.

In this contribution, we will provide detailed information about strategies, approaches and outcomes of the DARE activities, including information about where the recovered observations are freely accessible. Under the EURO4M-DARE effort, about 2.7M station-values of daily (sub-daily) maximum and minimum temperatures and precipitation (sea level pressure) observations were recovered from observing sites in North African, Middle East and Mediterranean countries.

The focus was placed on extending back in time those key records that have the potential to complete as far as possible the instrumental record, covering since the second half of the 19th century up to the present, while ensuring their quality. The dataset was made freely accessible through several international databanks and repositories.

Under the UERRA-DARE component, about 9M (~178M) of station values were recovered (gathered from open data sources in Catalonia, Norway and Sweden) over European data-sparse sub-regions for pre- and post-1950, while their quality and spatial homogeneity have also been ensured. In this case,

Data rescue activities to support reanalysis and climate services: the EU-funded UERRA and EURO4M projects approaches and outcomes

Author Manola Brunet

Affiliation Centre for Climate Change Universitat Rovira i Virgili

Co-authorsP. Jones (2), A. Gilabert (1), P. Unden (3), L. Ashcroft (1), J.R. Coll (1), A. Klein Tank (4) 1: Centre for Climate Change, University Rovira i Virgili, Tarragona, Spain, 2: Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom, 3: Sveriges Meteorologiska och Hydrologiska Institut (SMHI), Sweden, 4: Koninklijk Nederlands Meteorologisch Instituut (KNMI), Netherlands

In the last years and under the EU funding support, two research projects have significantly enhanced climate data availability and accessibility from land surface stations over Europe and adjacent regions.

The EURO4M (European Reanalysis and Observations for Monitoring) project (2009-2013) was aimed at supporting timely and reliable climate services to monitor variations and change of European climate, while the UERRA (Uncertainties in Ensembles of Regional Reanalysis) ongoing project (2014-

Section 2 – Observations for reanalyses

Preparing Observations for Reanalysis

Author Nick Rayner

Affiliation Met Office Hadley Centre

Dynamical reanalyses provide a complete representation of the observed state of the climate at a given point in time. The quality of that representation depends on many things, but it depends most fundamentally on the observations assimilated. In order to produce a reanalysis which represents the past variability and evolution of the climate as faithfully as possible, a large amount of work is required to prepare the observations before they can be used, either to provide boundary conditions or to be assimilated.

This overview presentation will consider the different types of work required (e.g. data rescue, quality control, homogenisation, uncertainty estimation) and use specific illustrative examples from the physical domain (atmosphere, ocean and cryosphere) from both satellite and in situ sources of observed information.


surface data only reanalyses) the overall quality of the adjustments could be improved as well.

Comprehensive comparisons with available satellite data and reanalysis data are provided. The potential impact of making radiosonde records consistent with reprocessed GPS-RO measurements in the 2006-2016 period is also assessed. The adjustments are expected to significantly reduce the rejection rate of radiosonde temperature observations as well as the biases of the resulting reanalyses such as the first Copernicus climate reanalysis ERA5.

It is well known that radiosonde data need bias correction before they can be used for climate reanalyses. Most reanalyses rely on bias corrections calculated offline using (semi)automatic homogeneity adjustment methods. One approach is to analyse subdaily time series of differences between background forecasts of a previous reanalysis cycle (bg) and observation records (obs) for break detection. For break adjustment, one can either use again the bg-obs time series or one can use composites of neighbouring radiosondes.

Adjustments from both methods (called RAOBCORE/RICH) have been used in many contemporary reanalyses assimilating these data. Since the last major release of this data set in 2012 several improvements could be realized, most notably the adjustment of annual variations of the radiosonde observation biases, better adjustment of short time series and of time series with gaps, backward extension of adjustments to 1939 and forward extension to 2016.

Backward extension has been greatly facilitated by activities at ECMWF to convert upper air data collected within the EU FP7 project ERA-CLIM(2) into the so-called ODB format, which can be directly read in by the Copernicus reanalysis data assimilation system and is convenient for other use cases as well. Due to availability of better reference data (ERA-preSAT, JRA-55 and also

systems and outdated file formats. They lack any metadata standards and each product is often written in its own proprietary file structure. This requires creating metadata by reading the contents of the old data files.

The job is tedious and laborious, as documentation may be incomplete, data files and tapes are sometimes corrupted, or were improperly copied at the time they were created.

Homogenized radiosonde temperature data for climate reanalyses

Author Leopold Haimberger

Affiliation University of Vienna

Co-authorsH. Hersbach (European Centre for Medium-Range Weather Forecasts, UK), P. Dahlgren (European Centre for Medium-Range Weather Forecasts, UK), S. Brönnimann (Oeschger Center for Climate Change Research, University of Bern, Switzerland) S. Jourdain (Météo-France, France), Florian Ladstätter (Wegener Center for Climate and Global Change, University of Graz, Austria) A. Steiner (Wegener Center for Climate and Global Change, University of Graz, Austria), A. Sterin (Russian Research Institute for Hydrometeorological Information, Russia), A. Stickler (Oeschger Center for Climate Change Research, University of Bern, Switzerland), M.A. Valente (Instituto Dom Luiz, Faculty of Science of the University of Lisbon, Portugal)

Data Recovery Effort of Nimbus era Observations by the NASA GES DISC

Author James E. Johnson

Affiliation ADNET/NASA GES DISC

Co-authorsAsghar Esfandiari (1,2), Emily Zamkoff (1,3), Atheer Al-Jazrawi (1,4), Irina Gerasimov (1,2), Gary Alcott (1). 1: Goddard Earth Sciences Data and Information Services Center (GES DISC), NASA GSFC, Greenbelt, MD, United States. 2: ADNET Systems, Inc., Rockville, MD, United States. 3: KBR Wyle Systems, Inc., McLean, VA, United States. 4: Telophase Corporation, Arlington, VA, United States.

NASA launched seven Nimbus meteorological satellites in the 1960s and 70s. These satellites carried instruments for making observations of the Earth in the visible, infrared, ultraviolet, and microwave wavelengths. The original data archive consisted of a combination of magnetic tapes and various film media. As these media are well past their expected end of life, the valuable data they contain are now being migrated to the GES DISC modern online archive

The process involves recovering the digital data files from the tapes as well as scanning images of the data from film strips. This presentation will address the status and challenges of recovering the Nimbus data. The old data products were written on now obsolete hardware

Section 2


impact of any conversions on data quality. Secondly a comparison of duplicate observations originating from the same original report, but subject to differences in data management, would enable an improved assessment of this contribution to data uncertainty.

Other anticipated benefits of reprocessing include recovery of additional data and metadata and improved consistency.

EUMETSAT Data Records in Support of Reanalysis

Author Jörg Schulz

Affiliation EUMETSAT

Co-authorsC. Anderson (EUMETSAT), M. Doutriaux-Boucher (EUMETSAT), T. Hanschmann (EUMETSAT), Tim Hewison (EUMETSAT), V. O. John (EUMETSAT), A. Lattanzio (EUMETSAT), C. Marquardt (EUMETSAT), R. Roebeling (EUMETSAT), F. Rüthrich (EUMETSAT), and T. Tabata (MSC/JMA)

EUMETSAT addresses climate monitoring by delivering advanced multi-satellite programmes with long-term commitment, maintaining a unique archive of decades of space-based observations, producing consistent climate data records, providing easy access and supporting climate-related capacity building initiatives. This involves specific scientific and technical efforts

construction of marine climate records and in reanalysis.

ICOADS provides open access to a surface marine data from a variety of different platform types (including ships, moored and drifting buoys and fixed platforms) and importantly keeps the multivariate marine record together in a common format. In recent years the importance of identifying observations made on the same ship or platform has become more apparent as the sophistication of error models for marine data has increased. Identification of the observations made on the same platform is also a key requirement for reanalysis. Unfortunately the marine data in ICOADS contains many observations without identifiers as substantial amounts of historical data were derived from sources that had not retained ship identifier information.

We will illustrate, using examples from a probabilistic trajectory estimation, how the methods used to combine marine surface data from different historical archives can affect quality and consistency. Focussing on requirements for reanalyses, we will demonstrate how reprocessing of historical marine surface data holdings would improve the quality of the marine climate record.

A reprocessing would permit an improved quantification of uncertainty. Firstly a review of the available documentation and formats would provide additional information on data precision and the

We shall present the overarching plans for service provision, and highlight the progress to date in creating an inventory of data holdings from disparate available sources. We shall highlight an initial forthcoming test release of the data and the schedule of further releases. The service must meet key stakeholder needs if it is to be successful. Therefore we strongly welcome constructive feedback both during and after the event. Formal channels for feedback will be highlighted.

The benefits for reanalysis of reprocessing the surface marine climate record

Author Elizabeth C. Kent

Affiliation National Oceanography Centre

Co-authorsD. I. Berry (National Oceanography Centre), E. Freeman (National Centers for Environmental Information), S. J. Worley (National Center for Atmospheric Research)

The surface marine observational record is an important input data source for all reanalyses. The observations are used for assimilation, but for atmospheric reanalyses are also used for construction of sea surface temperature gridded analyses used as the lower boundary. The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is the most complete archive of surface marine observations and is widely used in the

The Copernicus Climate Change Service Global Land and Marine Observations Database: Plans and progress to date

Author Peter W. Thorne

Affiliation Maynooth University

Co-authorsC. Voces (Maynooth University), M. J. Menne (NOAA NCEI), E. Freeman (NOAA NCEI), R.J.H. Dunn (Met Office), D. Berry (NOC), A. Stephens (STFC)

The Copernicus Climate Change Service Global Land and Marine Observations Database service aims to produce improved surface meteorological data holdings across domains, timescales, and Essential Climate Variables. Substantial efforts will be made to integrate holdings, ensuring consistency across and between timescales (sub-daily, daily and monthly), and to improve aspects of data discovery and access.

The data shall be served to users under a common data model as a set of fundamental data holdings suitable for use in myriad applications, including reanalyses. The service started in March 2017 and, subject to satisfactory performance, shall run for four years with incremental improvements in service provision over its lifetime. It brings together a number of key European organisations together with sustained in-kind collaboration with NOAA’s National Centers for Environmental Information.

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have been inter-calibrated to the SSM/I instrument series to allow a seamless continuation of existing TCDRs.

In order to extend the available FCDR to the time period before the SSM/I epoch, CM SAF has now reprocessed available brightness temperatures from the SMMR (Scanning Multichannel Microwave Radiometer) on board Nimbus-7 with the main focus on the inter-calibration of the brightness temperatures to the SSM/I series, using ERA20c as a transfer target. The re-processed data record will be available in the same user friendly data format as the existing FCDR. The new FCDR release will also extend the SSMIS data record with two additional years. Altogether, the FCDR will now span the time period from 1978 to 2015 combining observations from SMMR, SSM/I and SSMIS.

This presentation will focus on the inter-calibration of the SMMR and the evaluation of the combined FCDR over the complete time period. A validation of the brightness temperatures is a challenging task as there are no ground-truth reference measurements available for the microwave band. Hence, the homogeneity of the FCDR is evaluated by an analysis of the relative biases between the different instruments before and after the inter-calibration offsets are applied.

In order to derive reliable long term trend estimates of the global water and energy cycle parameters it is strictly necessary to carefully correct for all known problems and deficiencies of the SSM/I radiometers as well as to inter-calibrate and homogenise the different instruments. Moreover, all applied corrections need to be clearly documented to provide a complete calibration traceability for a Fundamental Climate Data Record (FCDR).

Following these recommendations, CM SAF released in 2013 a FCDR of SSM/I brightness temperatures (DOI:10.5676/EUM_SAF_CM/FCDR_SSMI/V001), freely available from the web user interface (http://wui.cmsaf.eu/). This FCDR has already been used in the ESA CCI Sea ice project and will also be used in the upcoming reanalysis ERA5. In order to further extend the HOAPS dataset in time, the SSM/I successor instrument SSMIS (Special Sensor Microwave Imager Sounder) has to be used from 2009 onwards.

CM SAF also reprocessed the SSMIS sensors onboard F16, F17, and F18 to the same standards as the SSM/I data record for the time period 2006 – 2013 and the combined FCDR was released in 2015 (DOI:10.5676/EUM_SAF_CM/FCDR_MWI/V002). Amongst others, known instrument issues like sunlight intrusions, moonlight intrusions, and reflector emissivity have been accounted for and the brightness temperatures

addition, EUMETSAT is also providing Atmospheric Motion Vector data records from Meteosat and AVHRR data that have been consistently reprocessed for the usage in re-analysis.

The presentation will provide an overview of EUMETSAT’s recent scientific and technical advances and prospects for providing useful satellite data records for reanalysis.

A Fundamental Climate Data Record of SSM/I, SSMIS, and SMMRbrightness temperatures

Author Karsten Fennig

Affiliation Deutscher Wetterdienst

Co-authorsMarc Schröder (DWD, Offenbach, Germany), Axel Andersson (DWD, Hamburg, Germany)

The satellite based HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data; http://www.oaps.org/) climatology provides climate data records of precipitation, evaporation and the resulting freshwater flux over the global ice-free ocean between 1987 and 2008. The latest version of HOAPS has been released by CM SAF and is available from the CM SAFs web user interface (http://wui.cmsaf.eu/). The HOAPS climate data records are primarily based on passive microwave measurements from the SSM/I (Special Sensor Microwave/Imager) sensor family.

for the re-calibration of historical satellite data and the extraction of climate data records.

In particular, the scientific analysis of raw satellite data leading to corrections of artefacts, improved calibration of individual instruments and harmonisation of several satellite instruments in a time series is fundamental to serve the generation of physically consistent data records of geophysical variables by reanalysis or the application of retrieval methods. With the participation in the EU ERA-CLIM, ERA-CLIM2 and FIDUCEO projects EUMETSAT has developed dedicated capabilities and capacities to deliver consolidated Fundamental Climate Data Records useful for global reanalysis.

The developments are utilised in support to the Copernicus Climate Change Service where EUMETSAT is delivering further consolidated data records for many of its own satellite missions but also for satellites instruments from other space agencies ranging back into the late 1970s. The instrument records addressed range from infrared and microwave sounding and imaging, radio occultation to scatterometer instruments.

For instance instruments considered for infrared sounding range from historic HIRS on NIMBUS-6 to the modern IASI on Metop platforms. For each of the data records significant improvements in calibration, multi-instrument time series harmonisation and/or uncertainty characterisation has been achieved. In

Section 2


exposition. In view of the already available 15 years of data acquired by the GRACE mission and the prospect of a continuation of the gravity-based monitoring of terrestrial water storage with GRACE-FO, which is scheduled for launch in February 2018, it is now very promising to attempt the incorporation of gravity-based indicators into hydrometeorological re-analysis efforts.

This presentation will provide an overview on the current accuracy of GRACE-based water storage estimates and will demonstrate by means of a number of dedicated examples the potential value of satellite gravimetry when compared to other availabe observations of the terrestrial branch of the water cycle.

Observing Mass Variability in the Earth System with the Satellite Gravity Missions GRACE and GRACE-FO

Author Henryk Dobslaw

Affiliation Helmholtz Centre Potsdam, German Research Centre for Geosciences

The satellite mission GRACE was specifically designed to map the Earth’s time variable gravity field: since 2002, two twin satellites are trailing each other with a distance of 220 km at a very low altitude of about 400 km in a near-polar orbit. Continuous distance measurements between the spacecraft allow for the mapping of the gravity potential from data accumulated over 30 days only, thereby providing a time-series of the global mass distribution at and beyond the Earth’s surface with monthly resolution.

Over the continents, time-variations in the gravity field as observed by GRACE are dominated by changes in the water masses in different hydrological storages, which includes surface water, snow mass, soil moisture at various depth levels, and even groundwater residing in the deep aquifers.

GRACE is therefore unique among the currently available remote sensing concepts since it is susceptible to mass changes independently of its surface

Section 2


(20th century coupled climate reanalysis system supported by the EU ERA-CLIM and ERA-CLIM2 R&D projects).

All systems are using a 10-member ensemble, on which uncertainty estimates are based. The presentation will focus on the diagnosis of the uncertainty information as provided by these EDA systems. Some relevant specific scientific questions will be discussed as for example the spatial-temporal variability of the reanalysis uncertainty information or how uncertainties in the verifying truth can influence the validation of uncertainty estimation. Finally guidance will be given how this information can be best used for the reanalysis user community.

Impact of Optimal Assimilation Windows in Coupled Data Assimilation on AMOC Analysis

Author Shaoqing Zhang

Affiliation Ocean University of China

Co-authorsLv Lu, Xiaopeilin and Lixin Wu (Physical Oceanography Key Laboratory of Ministry of Education, Ocean University of China, and Qingdao National Laboratory for Marine Science and Technology)

Climate signals are the results of interactions of multiple time scale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and

Uncertainty estimation in modern reanalysis systems

Author Andras Horanyi

Affiliation ECMWF

Co-authorsG. Biavati (ECMWF), P. Dahlgren (ECMWF), H. Hersbach (ECMWF), J. Muñoz-Sabater (ECMWF), and R. Radu (ECMWF)

Uncertainty information is an integral part of any meteorological analysis and prediction system and provides essential added value to the users. Estimates of uncertainty are also important in reanalysis but are not provided with all currently available data sets. At the European Centre for Medium-Range Weather Forecasts (ECMWF) various reanalysis systems have been produced to date, or are currently in production, which includes uncertainty estimates.

This is possible by using the Ensemble of Data Assimilation (EDA) technique. The EDA system provides flow-dependent background errors for the data assimilation system in the reanalysis, but in addition, the spread of the EDA can also be used for uncertainty estimates of the reanalysis products. ECMWF is in the production phase of ERA5 (implemented by the Copernicus Climate Change Service on behalf of the European Commission) and has produced the ERA-20C and CERA-20C reanalyses

Minimization of this Lagrangian is achieved through adequate variation of elements of the very high-dimensional uncertainty or control space(consisting initial and boundary conditions as well as model parameter fields) as informed by the adjoint model. As practiced by the “Estimating the Circulation and Climate of the Ocean” (ECCO) consortium and targeting the era of global coverage by satellite altimetry, the optimal state and parameter estimates fulfill conservation laws exactly over the full multi-decadal estimation period, as it avoids unphysical analysis increments at regular periods throughout the estimation process.

Closed property budgets so inferred provide valuable information for ocean and climate science. Remaining systematic misfits or unphysical control adjustments point to either remaining model inadequacies or unrealistic uncertainty estimates.

The sustained multi-decadal production effort by ECCO is entering a new phase with a special emphasis on the ocean’s impact on, and the imprints from the interaction with the polar ice sheets, and their role in global and regional sea level change.

Section 3 – Methods for reanalyses

Dynamically and kinematically consistent global ocean state and parameter estimation in support of climate research

Author Patrick Heimbach

Affiliation University of Texas at Austin

Understanding the global full-depth ocean circulation, attributing its evolution and changes on seasonal to multi-decadal time scales, inferring its role in the global climate system, and quantifying related uncertainties are hampered by sparse and heterogeneous observations, an inherently turbulent fluid, imperfect models, and uncertain forcing functions.

Viewed as a very large-scale estimation problem, the goal is to find an optimal state and parameter estimate through fitting a state-of-the art circulation model to all available observations while fulfilling underlying conservation laws and equations of motion. To do so we formulate a variational problem in which a weighted squared model-data misfit function is augmented by the model equations via Lagrange Multiplier Method.


component of MERRA-2 used a 3D-Var scheme, which was operational at the time of its design. Since then, a Hybrid 3D-Var then a Hybrid 4D-EnVar were implemented, adding an ensemble component to the data assimilation scheme.

In this work, we will be examining the benefits of using hybrid ensemble flow-dependent covariances to represent errors and uncertainties in historic periods. Specifically, periods of pre- and post-satellites, as well as periods of active tropical cyclone seasons.

Finally, we will also be exploring the use of adaptive localization scales.

A Method for Snow Reanalysis: The Sierra Nevada (USA) Example

Author Manuela Girotto

Affiliation USRA & NASA GMAO

Co-authorsSteven A. Margulis (Department of Civil and Environmental Engineering, University of California, Los Angeles, CA, USA), Gonzalo Cortés (Department of Civil and Environmental Engineering, University of California, Los Angeles, CA, USA), Michael Durand (School of Earth Sciences, and Byrd Polar Research Center, The Ohio State University, Columbus, Ohio, USA)

This work presents a state-of-the art methodology for constructing snow water equivalent (SWE) reanalysis. The method

model error forcing term active in the stratosphere above 40 hPa, and show results of assimilation trials using the ECMWF IFS atmospheric model. Results show improvements in the short-range forecast fits to observations, and this formulation of weak-constraint 4D-Var was made operational at ECMWF in November 2016.

Attempts to extend the model error forcing to the rest of the atmosphere have so far been unsuccessful due to problems with erroneous interpretation of aircraft observation error as model error. Characterising the statistical properties of model error is one of the main current problems in the weak-constraint 4D-Var. Future work will aim to improve the specification of the model error covariance matrix. We discuss results from an investigation into 4D-Var window length, 12 hour vs 24 hour, with both strong- and weak-constraint 4D-Var.

Using hybrid data assimilation for reanalyses

Author Amal EL Akkraoui

Affiliation NASA-GMAO/SSAI

Co-authorRicardo Todling (NASA-GMAO)

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) is the latest reanalysis produced by GMAO, and provides global data spanning the period 1980-present. The atmospheric data assimilation

The ECMWF weak-constraint 4D-Var formulation and a comparison between 12 and 24 hour assimilation window length to produce recommendations for future reanalysis as part of the ERACLIM2 project

Author Jacky Goddard

Affiliation ECMWF

Co-authorsP. Laloyaux (ECMWF), M. Fisher (ECMWF – retired), Y Trémolet (NCAR/UCAR), S. Lang (ECMWF)

In most operational implementations of four-dimensional variational data assimilation (4D-Var) the strong-constraint formulation is used. This relies on the assumption that the numerical model’s representation of the evolution of atmospheric flow is perfect, or at least that the model errors are small enough to be neglected compared to other errors in the system.

As other aspects of data assimilation processes have advanced, the validity of this perfect model assumption has become more questionable. It also limits the length of the atmospheric analysis window that can be used to roughly 12 hours.

Weak-constraint 4D-Var relaxes the perfect model assumption by explicitly representing model error as part of the 4D-Var control variable. We present a formulation of weak constraint with a

coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model.

Given different time scales of characteristic variability in different media, an optimal assimilation window (OAW) exists for each medium. With a simple coupled model that simulates typical scale interactions in the climate system, we first show that an OAW in each medium can provide maximal observational information that best fits characteristic variability of that medium during the data belending process.

Then we apply the idea to a coupled general circulation model and its data assimilation system to study the impact of OAWs on climate analysis by recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean more accurately. In particular, the features and variability of Atlantic Meridional Overturning Circulation has been examined.

Section 3


hypotheses about the mechanisms ruling past changes or the compatibility of the interpretation of observations coming from different sources. Examples are provided, in particular focusing on the temperature asymmetry between continents in both hemispheres over the last centuries, showing the role of the oceanic heat storage and transport to explain the delayed warming of the Southern Ocean compared to other regions.

A global climate reconstruction using data assimilation

Author Stefan Brönnimann

Affiliation Oeschger Centre and Institute of Geography, University of Bern

Co-authorJ. Franke (Oeschger Centre and Institute of Geography, University of Bern)

Understanding the past behaviour of the climate system ideally relies on a comprehensive view of past climate states. However, paleoclimatology is often faced with a sparsity of proxies and a comprehensive view is then only possible with audacious interpretation.

In recent years, new numerical techniques have become available that derive a best estimate of the climate state by combining the real-world information from sparse proxy data with the physics of climate models. Such data sets provide a physically consistent, spatially

Paleoclimate reanalyses as a tool to understand the signal recorded by observations over the past millennium

Author Hugues Goosse

Affiliation Université de Louvain ELIC/TECLIM

Data assimilation has attracted increasing interest in the paleoclimate community over the past 15 years since the technique has several advantages compared to the empirical-statistical approaches traditionally used to reconstruct temperature or precipitation fields from paleoclimate records. Several issues still need to be addressed to obtain comprehensive reanalyses, one of the strongest constraint being the small number of observations, displaying relatively large uncertainties.

Those records are generally only indirectly connected to standard climate variables implying that inversion techniques or adequate observation operators need to be included in the assimilation process. Specific adaptations to data assimilation algorithms are also required to deal with the records that represent averages over periods ranging from a few months to several decades and are distributed over strongly spatially biased network.

Nevertheless, existing simulations with data assimilation already provide useful reconstructions of the state of the system. They also provide a way to test

Atmospheric reanalysis for multi centuries using historical weather archives and isotopic proxies

Author Kei Yoshimura

Affiliation The University of Tokyo

Co-authorsP. Neluwala (The University of Tokyo), A. Okazaki (RIKEN)

Our systematic instrumental measurement for meteorological quantities only lasts 100 years at most, so they are too short to analyze recent big climate changes, like Little Ice Age or Medieval Warming Period. In our research group, we have made an offline data assimilation system for stable water isotopes and showed our success to reproduce ENSO changes during 19th to 21st century (Okazaki and Yoshimura, 2017).

On the other hand, we have made data assimilation of weather information from old diaries (Toride et al., 2017). Thus, by combining those two data assimilation methods, we are trying to make multi-centennial length atmospheric reanalysis product. At the presentation, I’d like to introduce these two new methods and current status of our multi-centennial reanalysis project.

is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series.

This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data from the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlation greater than 0.95 compared with in situ SWE observations.

The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (31 years), and accuracy provide a unique dataset for investigating snow processes. This presentation illustrates how the reanalysis dataset was used to provide a basic accounting of the stored snowpack water in the Sierra Nevada over the last 31 years and ultimately improve real-time streamflow predictions.

Section 3


At the same time, there are undesirable discontinuities in ocean heat content and an excessive accumulation of Arctic sea ice. CERA-20C provides a ten-member ensemble climate reanalysis for all parameters and levels over the 20th century. Ensemble generation is based on the Ensemble of Data Assimilations (EDA) system which explicitly accounts for errors in the observational record and in the forecast model. This ensemble technique aims to provide an indication of the confidence in the data.

NOAA and discuss its preparation and challenges for assimilation of data with strong diurnal signals in the MLT region.

Earth system climate reanalyses at ECMWF

Author Patrick Laloyaux

Affiliation ECMWF

Co-authors Eric de Boisseson, Per Dahlgren, Dinand Schepers, Jacky Goddard, Yuki Kosaka, Magdalena Balmaseda, Kristian Mogensen, Dick Dee, Roberto Buizza (ECMWF)

The European Centre for Medium-Range Weather Forecasts is a key player in the production of reanalyses for climate monitoring and research. Following the Earth system approach embraced in the new ten year strategy, a coupled assimilation system that ingests simultaneously ocean and atmospheric observations in a coupled ocean-atmosphere model has been developing.

This approach has been used to produce a new coupled 20th-century reanalysis, called CERA-20C, which provides a long record of low-frequency climate variability using a consistent set of observations. First results show that CERA-20C improves on the representation of atmosphere–ocean heat fluxes and of mean sea level pressure compared to previous reanalyses.

with the ionosphere models depends on the comprehensive extension of data assimilation methods into the Mesosphere and Lower Thermosphere (MLT).

In this region of active wave dynamics and strong diurnal cycles the past (UARS) and present (TIMED, EOS-Aura) space-borne observations of wind, temperature and tracers have been analyzed by models with the top lids placed between 80-100 km for case studies. The relatively low positions of the model top lids and 6-hour assimilation windows preclude accurate analysis for diurnal and sub-diurnal upward-propagating tides that deliver impacts of “terrestrial” perturbations and stratospheric climate anomalies into the space weather/climate domain.

In this paper we discuss methods to constrain the dynamics and transport of the multi-year WA predictions below the stratopause using the 2007-2016 MERRA data to achieve the first outlook on the day-to-day, annual and year-to year variations of the mean flow, planetary waves and tides. We will verify realism of two WAM predictions of NOAA and NCAR constrained by MERRA by MLS, TIDI and SABER observations along with ground-based measurements.

The last decade (2004-present) collections of the MLT data from the space and ground provide us opportunity to explore their reanalysis in WA models. We overview the current status of data analysis studies in the WAM/WDAS of

complete picture of the past climate system that is in agreement with the proxy records within their errors.

We present a 400-year long, monthly, global, 3-dimensional climate data set that was produced by assimilating historical instrumental data, documentary evidence, and tree ring data into a large ensemble of climate model simulations using an off-line Ensemble Kalman Filter technique. In addition to evaluations and comparisons of this method with existing reconstruction, we present analyses of this data sets with respect to the transition of the climate system from the Little Ice Age climate to the present climate.

Reanalysis in the Whole Atmosphere Models: From Nudging Techniques to Data Analysis in the Mesosphere and Lower Thermosphere

Author Valery Yudin

Affiliation Colorado University, CIRES

Co-authorsD. Kleist (NCEP/EMC), K. Howard (NCEP/EMC), T. Fuller-Rowell (CU/CIRES), S. Karol (CU/CIRES), R. Akmaev (NOAA/SWPC), A. Kubaryk (NCEP/EMC).

The Whole Atmosphere Model (WAM) framework assigns to link the terrestrial and space weather and climate applications. Current advances in the WAM developments and in their coupling

Section 3


Thus, the fidelity of reanalysis stratospheric WV is sensitive to how accurately the fundamental drivers of stratospheric WV such as tropical tropopause layer temperatures, methane oxidation, and the stratospheric overturning circulation are represented. Because of these issues and the known deficiencies in the representation of stratospheric transport in reanalyses, we find much poorer agreement both amongst reanalyses and between reanalyses and independent observations. For these reasons, stratospheric WV from the current generation of reanalyses should generally not be used in scientific studies.

Preliminary assessment of the ERA5 ozone reanalyses

Author Rossana D. Dragani

Affiliation ECMWF

Co-authorsH.H. Hersbach (ECMWF), C.S. Soci (ECMWF)

ECMWF is currently producing the ERA5 reanalysis that will replace the widely-used ERA-Interim atmospheric reanalysis. Produced as part of the EU-funded Copernicus Climate Change Service, ERA5 will be open and freely available to all. The ERA5 reanalysis is based on a significantly different and, in general, much-improved data assimilation system compared to its predecessor, including in its ozone component.

existing global reanalyses, and whether or not significant differences exist amongst them.

We present results from the WV and O3 intercomparisons that were performed as part of the SPARC (Stratosphere-troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP).

Comparisons are made over a range of timescales between the different reanalyses, and between reanalyses and observational datasets. In addition to the intercomparisons, we discuss the treatment of WV and O3 in reanalyses to aid future research and guide the interpretation of differences between the reanalysis fields. Because total column ozone (TCO) is assimilated in the newer reanalyses, these reanalyses generally reproduce TCO well except when data coverage is lacking, such as during polar night.

We find that the vertical distribution of ozone is relatively well represented in reanalyses, particularly given that for most reanalyses there are only weak constraints on the vertical profile of ozone from observations and that most have a simplistic representation of ozone photochemical processes. In contrast to O3, stratospheric WV data are not currently assimilated, with humidity observations typically used only in the troposphere below a specified vertical level at or near the tropopause.

products by establishing collaborative links between reanalysis centres and data users.

The emphasis is on diagnostics of the upper troposphere, stratosphere, and lower mesosphere. In the talk, an overview of the S-RIP activity during 2013-2017 is made, and some scientific highlights are presented and discussed.

Assessment of upper tropospheric and stratospheric water vapor and ozone in reanalyses as part of S-RIP

Author Sean M. Davis

Affiliation NOAA ESRL

Co-authorsM.I. Hegglin (Univ. Reading), M. Fujiwara (Hokkaido Univ.), R. Dragani (ECMWF), Y. Harada (JMA), C. Kobayashi (MRI/JMA), C. Long (NCEP/NOAA), G.L. Manney (NWRA/New Mexico Tech.), E. Nash (SSAI), G.L. Potter (NASA GSFC), S. Tegtmeier (GEOMAR), T. Wang (NASA JPL), K. Wargan (NASA GMAO), J.S. Wright (Tsinghua Univ.)

Reanalysis datasets are widely used to understand atmospheric processes and past variability, and are often used as “observations” for comparison with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately these species are represented in the

Section 4 – Evaluation and intercomparisons of reanalyses

Results from the SPARC Reanalysis Intercomparison Project (S-RIP) during 2013-2017

Author Masatomo Fujiwara

Affiliation Hokkaido University

Co-authorsG. L. Manney (NWRA and New Mexico Tech, USA), L. J. Gray (Oxford Univ. and NCAS, UK), J. S. Wright (Tsinghua Univ., China), and the S-RIP team

The climate research community uses global atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere, yet different reanalyses may give very different results for the same diagnostics. The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP, https://s-rip.ees.hokudai.ac.jp) is a coordinated activity to compare reanalysis data sets using a variety of key diagnostics.

The objectives of this project are to identify differences among reanalyses and understand their underlying causes, to provide guidance on appropriate usage of various reanalysis products in scientific studies, particularly those of relevance to SPARC, and to contribute to future improvements in the reanalysis


Regional biases introduced by this shortcoming are order 20Wm-2 and strongest in the tropics. A second ambiguity arises from different reference states of water in the climate system: vapor at 0K in the atmosphere and liquid at 0°C in the ocean. Additionally, small inconsistencies in formulations of the energetics of current weather and climate models are highlighted. A more consistent energy budget framework is presented, which takes into account surface mass and associated enthalpy fluxes and is independent of reference temperature in the steady state.

Using atmospheric data from ECMWF’s ERA-Interim and JMA’s JRA-55 reanalyses, several resulting implications are illustrated. First, it is shown that material surface energy fluxes (including snowfall) globally have a net cooling effect on the Earth’s surface (-1.3Wm-2), with much larger regional values. This implies that the non-material (radiative plus turbulent) surface energy flux (FS) must be higher than previous estimates in order to balance the material surface energy flux and the observed ocean warming.

Second, the agreement between fields of FS inferred from satellite-measured radiation and reanalysis-based divergence of atmospheric lateral energy transports with independent surface flux products is substantially improved when using the here-presented instead of the commonly used budget formulation.

year older. Such large disagreements of AoA values are found in the whole stratosphere.

The time evolution also differs considerably depending on the reanalysis considered, e.g. JRA-55 delivers AoA trends over 2002-2012 which are nearly insignificant in the Northern Hemisphere and display no detectable dipole structure between the two hemispheres. Hence the multi-annual to multi-decadal evolution of AoA depicted by modern reanalyses is not yet sufficiently clear or consistent to be used as a diagnostic for the evaluation of chemistry-climate models.

Towards consistent diagnostics of the coupled atmosphere and ocean energy budgets

Author Michael Mayer


Co-authorsL. Haimberger (University of Vienna), J. Edwards (UK Met Office), P. Hyder (UK Met Office)

The widely used diagnostic vertically integrated total energy budget equations of atmosphere and ocean are re-examined and several inconsistencies are revealed. First, there is a dependence on reference temperature because enthalpy fluxes associated with precipitation and evaporation (material surface energy fluxes) are usually neglected.

multi-decadal timescales it is expected to decrease with rising levels of greenhouse gases in the atmosphere. Satellite observations of stratospheric tracers SF6 and HCl indicate that AoA did decrease in the Southern Hemisphere during the first decade of this century but also that it increased in the Northern Hemisphere.

This dipole structure of AoA trends has been confirmed by transport simulations driven by the ERA-Interim reanalysis but not by in situ observations in the stratospheric northern mid-latitudes, which have not yet delivered any significant trend over a forty-year time period. Hence further research is required about the magnitude, distribution and detectability of AoA trends. As part of the SPARC Reanalysis Intercomparison Project (S-RIP), we have developed a pre-processor to feed a Eulerian transport model with any of the available global (re-)analysis datasets.

This allowed us to compute the age of air in the stratosphere and its evolution from 1985 to 2015, according to five modern reanalyses: ERA-Interim, JRA-55, MERRA, MERRA-2 and CFSR/CFSv2. Our results compare favorably with those published previously using ERA-Interim. It turns out that the other reanalyses deliver surprisingly different and diverse results. For example at 20km height and for year 2000, JRA-55 delivers AoA up to one year younger than ERA-I while MERRA delivers AoA up to one

The ERA5 ozone reanalyses benefit from largely reprocessed datasets, many of which were generated with special attention to climate and reanalyses applications, e.g. those retrieved as part of the ESA-funded Climate Change Initiative. Compared to ERA-Interim, ozone-sensitive radiances in the infrared (IR) from several IR sounders are assimilated in ERA5.

A variational bias correction model was implemented for ozone observations to improve the data exploitation and remove potential inter-instrumental biases that normally affect different datasets of the same quantity causing a loss of performance when jointly assimilated.

In this contribution, we will first introduce the ERA5 ozone system, and discuss the differences from its predecessors, and then present some results from a preliminary assessment of the quality of the ERA5 ozone reanalyses.

Mean age of stratospheric air since 1985: large disagreements between five modern reanalyses

Author Simon Chabrillat

Affiliation BIRA-IASB

Co-authorsY. Christophe (BIRA-IASB), C. Vigouroux (BIRA-IASB), Q. Errera (BIRA-IASB), E. Mahieu (U. Lg)

Chemistry-climate model simulations have shown that the mean age of stratospheric air (AoA) is a good indicator of the strength of the residual circulation, and that at

Section 4


to isolate the effect of soil moisture on atmospheric conditionse estimate and compare soil moisture-temperature coupling strength using re-analysis data (ERA-Interim/Land, MERRA-2) on the one hand and a dataset combination that includes remote sensing data and gridded station observations on the other hand. For the relation between soil moisture and evaporative fraction three key parameters are estimated: 1) the frequency of the occurrence of different soil moisture regimes, 2) the sensitivity of evaporative fraction to soil moisture variations in the transitional soil moisture regime, and 3) the critical soil moisture value which separates water- and energy-limited evapotranspiration regimes.

All used datasets agree well in the overall geographical distribution of the single soil moisture regimes, but there are differences in the classification in some distinct regions. Regarding the sensitivity of evaporative fraction to soil moisture variations, all datasets reveal similar patterns, but the absolute values vary between the different datasets.

Eventually, the analysis allows to estimate the effect that soil moisture variations have on near-surface air temperature. While the different datasets agree well on the magnitude (typical soil moisture variations can impact air temperature by several kelvin), there are apparent differences in the patterns between the re-analyses and the combined dataset, especially in Africa and South America.

naturalized streamflow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim/Land, somewhat lower for MERRA-Land, and lower still for MERRA.

Quantifying spatio-temporal variations of soil moisture control on surface energy balance and near-surface air temperature

Author Clemens Schwingshackl

Affiliation Institute for Atmospheric and Climate Science, ETH Zürich

Co-authorsM. Hirschi (Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland), S.I. Seneviratne (Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland)

Soil moisture plays a crucial role for the energy partitioning at the Earth’s surface. Changing shares of latent and sensible heat fluxes, caused by soil moisture variations, can affect both near-surface air temperature and precipitation. Here, we use a simple framework for the dependence of evaporative fraction (the ratio of latent heat flux over net radiation) on soil moisture to analyze spatial and temporal variations of land-atmosphere coupling and its effect on near-surface air temperature.

This framework allows to separate water-limited from energy-limited evapotranspiration regimes and thus

better than the precipitation generated by the atmospheric models within the cycling MERRA-2 system and the earlier MERRA reanalysis. Compared to 3-hourly TRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation.

Because correcting the precipitation within the coupled atmosphere-land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from the earlier, offline MERRA-Land reanalysis. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA.

A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. The MERRA-2 and MERRA-Land surface and root zone soil moisture skill vs. in situ measurements is slightly higher than that of ERA-Interim/Land and higher than that of MERRA (significantly for surface soil moisture).

Snow amounts from MERRA-2 have lower bias and correlate better against reference data than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim/Land. Seasonal anomaly R values against

Third, results imply that previous studies seriously underestimated cross-equatorial atmospheric and oceanic energy transports. Overall, the improved framework allows for unambiguous energy budget diagnostics based on reanalyses and will help to provide more reliable benchmark values for validation purposes

Land surface precipitation and hydrology in MERRA-2

Author Rolf H. Reichle

Affiliation NASA/GSFC

Co-authorsR. D. Koster (NASA/GSFC), C. S. Draper (NASA/GSFC and USRA/GESTAR), Q. Liu (NASA/GSFC and SSAI), M. Girotto (NASA/GSFC & USRA/GESTAR), S. P. P. Mahanama (NASA/GSFC and SSAI), G. J. M. De Lannoy (KU Leuven), and G. S. Partyka (NASA/GSFC & SSAI)

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), provides global, 1-hourly estimates of land surface conditions for 1980-present at ~50-km resolution. Outside of the high latitudes, MERRA-2 uses observations-based precipitation data products to correct the precipitation falling on the land surface.

This paper describes the precipitation correction method and evaluates the MERRA-2 land surface precipitation and hydrology. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is

Section 4


Improved SST-precipitation relationships in the CERA-20C coupled climate reanalysis

Author Xiangbo Feng

Affiliation Department of meteorology, University of Reading

Co-authorsKeith Haines, Chunlei Liu (Department of Meteorology, University of Reading, Reading, UK

ECMWF has recently produced the 20th century ocean-atmosphere coupled reanalysis CERA-20C, following on from the similar uncoupled atmosphere reanalysis ERA-20C. The local SST-precipitation relationships are an indicator of air-sea interactions at sub-seasonal timescales in CERA-20C and ERA-20C, and these are compared with observations using monthly data over 1979-2010.

In convective regions, the negative SST-precipitation correlations in observations are well captured in CERA-20C, while these are not well reproduced in ERA-20C, which is more likely to show positive correlations. It appears that in the coupled reanalysis ocean surface can cool down with less surface solar radiation associated with more precipitating clouds.

However, in the uncoupled data, the prescribed SST does not respond to atmosphere feedbacks. Consequently,

For more detailed investigations daily precipitation is clustered into events based on days with more than 1 mm precipitation. Here, only grid-points with more than 250 events were considered to have statistical sufficient quantity, which excludes very dry area like Sahara or very wet areas like Indonesia.

Not surprisingly, the regions with the strongest differences are also those with data scarcity, mountain regions with their Luv and Lee effects or monsoon areas. They all show a strong systematic difference and breaks within the time series. Differences based on ETCCDI diagnoses were detected particularly in regions with large precipitation totals especially in Africa in the ITCZ area and in Indonesia. The overall comparison reveals geo-spatially heterogeneous results with areas of similar precipitation characteristics, but there are also still areas that present a challenge.

Additionally, areas with matching precipitation totals do not necessarily show matching extreme value indices, or even the indices show inconsistent results depending on the region.

ensemble CERA-20C (ECMWF, 2017) are yielded from the projects ERA-Clim and ERA-Clim2.

The multi-decadal reanalyses cover more than one century from 1900 to 2010 and have a spatial resolution of about 125 km. The reanalyzes are produced by the ECMWF’s IFS forecast model, but for CERA-20C the IFS model for the atmosphere is coupled with the NEMO model for the ocean and to the LIM2 model for sea ice.

The in-situ products of the Global Precipitation Climatology Center (GPCC) were used as a reference: The Full Data Monthly (FDM) (Schneider et al., 2014) containing global land surface precipitation from 1901 to 2013 with monthly resolution, and the Full Data Daily (FDD) (Schamm et al., 2014) from 1988 to 2013 with daily resolution. For both data sets, the respective overlapping period was chosen for the evaluation, 23 years (1988-2010) for FDD and 110 years (1901-2010) for FDM with 1° spatial resolution.

Through annual and seasonal totals, a good global overview of the consistency and the quality of the modeled precipitation can be obtained by means of correlation and contingency table scores. Climate change indices (ETCCDI) for precipitation are calculated to determine extreme values and their temporal change (Peterson et al., 2001, Appendix A).

The results emphasize the role of soil moisture for atmosphere and climate and highlight that a proper integration of these processes in weather and climate models is crucial. Important efforts have been made in the recent years to create datasets for a more thorough investigation of land-atmosphere coupling. Yet, our results show that precise conclusions about the soil moisture-temperature coupling strength are still uncertain due to the limited availability of adequate observations.

Assessment of precipitation in the CERA-20C and ERA-20C reanalyses by means of precipitation gauge observations

Author Elke Rustemeier


Co-authorsM. Ziese, A. Meyer-Christoffer, U. Schneider, P. Finger, A. Becker (Deutscher Wetterdienst, Hydrometeorology, Offenbach am Main, Germany)

Precipitation is a difficult parameter for reanalyses models, but it also has a strong impact on our daily life. But since precipitation has not been assimilated into the reanalyses, it is possible to assess the predicted precipitation with independent observation. Both reanalysis, ERA-20C deterministic (Poli et al., 2015) and the 10-member

Section 4


Uncertainty in Reanalysis over Europe

Author Peter Jermey

Affiliation Met Office

Co-authorsRichard Renshaw, Jemma Davie (Met Office)

The Uncertainties in Ensembles of Regional ReAnalyses (UERRA) project has produced regional reanalyses of the atmosphere over Europe. The principal contributions of the Met Office (UK) to the project are a 12km deterministic reanalysis and a 20 member 36km ensemble reanalysis, both covering the satellite era. The scale of atmospheric features that can be represented by a gridded reanalysis is limited by the resolution of the model grid and its accuracy is dependent on observations, model and boundary conditions, which all contain uncertainty.

Activities to measure uncertainty in reanalyses have often been limited by the lack of available independent measures of the true state of the atmosphere, however such capability is highly desirable in order to inform a diverse set of users on the suitability of the data. If uncertainty is not transparent to users, they may assume the reanalysis data is certain or that the uncertainty does not vary.

Interannual variability of the distribution of thin/thick ice differs among the reanalyses, which questions the suitability of current sea ice reanalyses to initialize seasonal forecasts of the Arctic sea ice. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems, although the interannual variability of average velocity and Fram Strait ice export is reasonably well reproduced in all systems.

The simulated sea ice velocity seems directly impacted by the choice of dynamical model parameters, which is not obvious for sea ice thickness. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent relatively well. However, the ensemble can not be used to get a robust estimate of recent trends in the Arctic sea ice volume. Recent developments within the Polar Ocean Reanalyses Intercomparison Project (PORA-IP) will be mentioned, including updates of the analysis on Arctic sea ice with a more recent generation of ocean reanalyses, and insights on the representation of the Antarctic sea ice cover in global ocean reanalyses.

This presentation summarizes the evaluation of Arctic sea ice cover in global ocean-sea ice reanalyses conducted as part of the Clivar-GSOP/GODAE OceanView Ocean Reanalyses Intercomparison Project (ORA-IP). Analyses have been conducted on a set of 14 global reanalyses, among which 9 assimilated sea ice concentration data. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on the simulated Arctic sea ice concentration, thickness and velocity.

The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints imposed by direct assimilation of ocean and/or sea ice observations and prescribed or assimilated atmospheric forcing.

A large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. The spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates.

The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations.

in the coupled reanalysis the mean precipitation is better estimated over most of the tropical and subtropical oceans, although it is worse over South America. We discuss the physical mechanisms controlling the SST-precipitation relationship at sub-seasonal timescales and how this can also impact the longer-term variations and trends in precipitation in the coupled product.

An intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses from the project ORA-IP

Author Matthieu Chevallier

Affiliation CNRM, Météo France

Co-authorsGreg Smith (MRD, Environment Canada, Dorval, Canada), Frédéric Dupont (MSC, Environment Canada, Dorval, Canada), Jean-François Lemieux (CMC, Environment Canada, Dorval, Canada), Magdalena Balmaseda (ECMWF, Reading, UK), Keith Haines (NCEO, University of Reading, UK), Petteri Uotila (FMI, Finland), Hugues Goosse (Université de Louvain-la-Neuve, Belgium), François Massonnet (Université de Louvain-la-Neuve, Belgium), Gilles Garric (Mercator Océan, France), Doroteaciro Iovino (CMCC, Italy), Frank Kauker (AWI, Germany), the ORA-IP and PORA-IP teams.

Section 4


only 20th century reanalysis (20CR) to the much higher-resolution full-input JRA55 reanalysis of the 1959-2012 period, plus two large ensembles of model simulations of the period generated using the 20CR model with two different sets of SST and sea-ice boundary conditions.

The changes in extreme temperatures from the first to the second half of the period agree well among the reanalyses, although less well than the changes in mean temperatures. This is shown to be mostly due to disagreement in representing changes in the temperature variance. The model simulations capture the essence of the extreme changes in most regions, but differ more from the reanalyses than the reanalyses differ among themselves.

This adds credence to both the extreme changes inferred from the reanalyses and the beneficial impact of even just the surface pressure observations in constraining those reanalyses. Similar conclusions drawn from comparing changes in extreme daily precipitation statistics over the shorter 1979-2012 period will also be discussed.

Do reanalyses capture long-term changes in extreme weather statistics?

Author Prashant D. Sardeshmukh

Affiliation CIRES/University of Colorado and Physical Sciences Division/NOAA

Co-authorsG.P. Compo, A. Wang, C. McColl (all CIRES, University of Colorado and Physical Sciences Division/NOAA)

The ability of reanalyses to represent long-term changes in the climate system is often questioned, despite their advantages of filtering out observational error and local noise at the observation locations and of generating physically consistent estimates of other variables at other locations.

This is because these advantages are compromised by the sparseness and errors of the observations in the earlier parts of the record, which cause the reanalyses to be more heavily influenced by errors in the assimilating model’s guess fields, specified boundary conditions and radiative forcings.

The problem is relatively more serious for assessing changes in extreme weather statistics. We have addressed this issue by examining changes in the probabilities of extreme lower tropospheric 5-day averaged temperature anomalies in five global reanalyses ranging in complexity from the low-resolution surface-input

database. More than 800 on site measurement time series were employed to obtain a complete understanding of the performance of Reanalysis and derived WRF downscaled output in the context of wind industry applications.

We intend with this presentation to provide a comprehensive metrics of different Reanalysis projects (ECMWF Era-Interim and ERA5, MERRA2, CFS/CFSR and JRA55) and to map the climate quality for wind industry end-users. A large databank of over 800 site with windmast measurements was employed for the validation of modeled wind time series. The sites represent a large spectrum of flow complexity across different locations for most of the wind industry target markets.

In particular, time correlation, consistency and bias and RMSE are provided for different categories and locations. Comparison between raw Reanalysis data and 3km and 100m downscaled products will be presented to assess the added value of the augmented resolution.

By perturbing sources of uncertainty, the UERRA ensemble reanalysis estimates the uncertainty in the ensemble mean. This capability will be evaluated to demonstrate how reanalysis uncertainty varies with space, time and synoptic condition. The impact of the changing observing system over forty years will also be demonstrated.

800+ site validation of Reanalysis & downscaled wind conditions time series

Author Gil Lizcano

Affiliation Vortex

Co-authorsO. Lacave, Vortex, P. Casso, Vortex, A. Bosch, Vortext, A. Monternes, Vortex

Model data are employed at different stages of the windfarm development: country engagement, resource screening, site identification, preliminary feasibility studies and due diligence process. Over the last 5 to 10 years, Reanalysis and downscaled products have been adopted by the wind industry as a feasible solution to complement on-site measurements and to fill the lack of information demanded by a global maked with project developments in places as differents as North Chile, Anatolia complex mountains, North Sea or Kenyan valleys.

This work provides an global wide insight on the quality of wind conditions virtual time series based on latest Reanalysis

Section 4


The AFES-LETKF data assimilation system for an experimental atmospheric global ensemble reanalysis

Author Akira Yamazaki

Affiliation Japan Agency for Marine-Earth Science and Technology (JAMSTEC)

Co-authorsTakeshi Enomoto (Disaster Prevention Research Institute, Kyoto University), Takemasa Miyoshi (RIKEN Advanced Institute for Computational Science), Nobumasa Komori (Application Laboratory, JAMSTEC)

A global atmospheric data assimilation system called ALEDAS comprised of AFES (Atmospheric GCM for the Earth Simulator) and LETKF (Local Ensemble Transform Kalman Filter) has been developed and is used to generate the experimental atmospheric global ensemble reanalysis (ALERA) dataset available from January 2008 to January 2013, which has been prolonged toward near real time analysis.

With ALERA and ALEDAS, several OSE studies have been conducted to assess impacts of radiosonde observations obtained during some observational campaigns, especially on the Arctic and subtropical oceans. Recently we have also performed some weather predictability studies by using ALERA and/or the OSE reanalyses as initial values for AFES. In addition, a diagnostic technique called Ensemble Forecast

Sensitivity to Observations (EFSO) which can quantify how much each observation has improved or degraded the forecast without a data denial experiment has been recently implemented into ALEDAS. The preliminary results from EFSO will be compared against OSE.

Section 4


Stratospheric intrusion-influenced ozone air quality exceedences investigated in the NASA MERRA-2 Reanalysis

Author Katherine Emma Knowland

Affiliation Universities Space Research Association (USRA) GESTAR & NASA GMAO

Co-authorsL.E. Ott (NASA/GMAO, GSFC, Greenbelt, MD), B.N. Duncan (Laboratory for Atmospheric Chemistry and Physics, GSFC, Greenbelt, MD), Krzysztof Wargan (Science Systems & Applications, Inc. (SSAI); NASA/GMAO, GSFC, Greenbelt, MD)

Ozone near the surface is harmful to human health and is a result of photochemical reactions with both man-made and natural precursor pollutant sources. Therefore, in order to reduce near surface ozone concentrations, communities must reduce anthropogenic pollution sources.

However, the injection of stratospheric ozone into the troposphere, known as a stratospheric intrusion, can also lead to concentrations of ground-level ozone exceeding air quality standards. Stratospheric intrusions are dynamical atmospheric features, however, these intrusions have been misrepresented in models and reanalyses until recently, as the features of a stratospheric intrusion are best identified in horizontal resolutions of 50 km or smaller.

Reanalyses’ use in operational weather forecasting

Author Roberto Buizza

Affiliation ECMWF

In the past two decades we have seen an increased use of reanalysis in operational weather forecasting. Reanalyses provide initial conditions for reforecasts, i.e. forecasts re-run using operational systems for past cases, both to improve operational forecast products and to provide users with a more solid performance assessment of the accuracy and reliability of the operational forecasts. Examples of operational products generated using reforecasts are the ECMWF Extreme Forecast Indices for 2-meter temperature and precipitation.

They are defined by comparing the probability distribution function of forecast states computed using the most recent ECMWF ensemble of forecasts, and the model climatological distribution function computed using an ensemble of reforecasts initialized using reanalyses for the past 20 years.

Examples of performance estimation based on reforecasts initialized from reanalyses are the reliability diagrams of the ECMWF seasonal ensemble forecasts of sea-surface temperature anomalies in a set of tropical regions, e.g. covering the El Niño areas in the tropical Pacific Ocean. During this talk, I will review the use of reanalyses in the ECMWF operational production process.

its temporal changes from a combined use of ocean observing systems and numerical model techniques.

Moreover, ocean reanalysis systems deliver us a unique insight into the role of the oceans as energetic buffer and regulator through its capacity to absorb and to redistribute large amounts of heat. In addition, consistency checks through physical budget constraints with the combined use of climate observations (in situ, remote sensing) and tools (reanalysis, climate models) have a large potential to deliver a robust uncertainty assessment, to shed new light on unresolved climate science issues and to strengthen the exchange between multi-disciplinary experts all concerned with the energy flow through the climate system.

This talk will give an overview on the development of ocean climate indicators such as EEI from ocean reanalyses, their use for physical budget constraints, and the evaluation on the redistribution of ocean heat. Specific examples will be introduced and main outcomes and challenges are discussed.

Section 5 – Applications of reanalyses

Insights into the role of the oceans in the Earth energy budget from ocean reanalysis

Author Karina von Schuckmann


Improving the accuracy of estimates of Earth’s climate state and variability is critical for advancing our understanding and prediction of the evolution of Earth’s climate. The energy budget of the Earth is a key determinant for the state and evolution of climate on our planet. Perturbations of this budget from internal or external climate variations create a radiative flux imbalance at the top of the atmosphere.

This Earth Energy Imbalance (EEI) is shaped by several climate forcings, some of which occur naturally and some that are anthropogenic in origin. There is a current positive EEI, which is mostly caused by human activity, and which is driving global warming. The EEI can best be estimated from changes in ocean heat content, complemented by radiation measurements from space. Ocean reanalysis systems are critical for the evaluation of the EEI as they deliver a 3-D view on the interior of our oceans and


rainfall over the South Korea-Japan peninsula (June through August: JJA, Amita et.al 2017).

Delayed response over South as well as over East Asia is relayed through the central Pacific sea surface temperatures. A negative (positive) phase of SAM generates a wave-train which propagates from the sub-polar latitudes towards the equatorial latitudes associated with warming (cooling) over the central equatorial Pacific region.

This warming (cooling) induces an ascending (descending) motion over the central Pacific with descending (ascending) motion over the (i) Indian subcontinent through the zonal Walker circulation influencing the ISMR; (ii) Korea-Japan sector through the meridional Hadley circulation influencing the peak July-August monsoon over Korea-Japan. These findings have potential implications on the seasonal forecasts of both the South and East Asian summer monsoons.

Role of Southern Annular Mode on Asian Monsoon: Mechanisms through NCEP-NCAR Reanalysis

Author Amita Prabhu

Affiliation Indian Institute of Tropical Meteorology

Co-authorsR. H. Kripalani (Indian Institute of Tropical Meteorology), G. Pandithurai (Indian Institute of Tropical Meteorology)

The annular modes are the most important hemispheric scale patterns of climate variability in the northern and the southern hemisphere. The Southern Annular Mode (SAM) is characterized by a see-saw phenomenon between the sea level high pressure belt normally across ~400S and a low pressure belt across ~700S. SAM is also referred as a High-latitude Mode or the Antarctic Oscillation. SAM index is defined as MSLP 400S – MSLP 700S.

Based on the National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data spanning 31 years for the period 1983-2013, results reveal that while the February-March SAM has a significant positive relation with the subsequent Indian summer monsoon rainfall (June through September: ISMR; Amita et.al. 2016), the May-June SAM has a significant positive relation with the summer monsoon

Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), have become a pivotal tool to study the meteorology surrounding extreme precipitation events. Using days classified as an extreme precipitation events based on a combination of observational gauge and radar data, two techniques for the classification of these events are used to gather additional information that can be used to determine how events have changed over time using atmospheric data from MERRA-2.

The first is self organizing maps, which is an artificial neural network that uses unsupervised learning to cluster like patterns and the second is an automated detection technique that searches for characteristics in the atmosphere that define a meteorological phenomena. For example, the automated detection for tropical cycles searches for a defined area of suppressed sea level pressure, alongside thickness anomalies aloft, indicating the presence of a warm core.

These techniques are employed for extreme precipitation events in preselected regions that were chosen based an analysis of the climatology of precipitation.

Classification of Meteorological Influences Surrounding Extreme Precipitation Events in the United States using the MERRA-2 Reanalysis

Author Allison Collow

Affiliation Universities Space Research Association (USRA) & NASA GSFC

Co-authorsM. Bosilovich (NASA GSFC), and P. Ullrich (UC Davis)

Extreme precipitation events can have a large impact on society through flooding that can result in property destruction, crop losses, economic losses, the spread of water-borne diseases, and fatalities. Observations indicate there has been a statistically significant increase in extreme precipitation events over the past 15 years in the Northeastern United States and other localized regions of the country have become crippled with record flooding events, for example, the flooding that occurred in the Southeast United States associated with Hurricane Matthew in October 2016.

Extreme precipitation events in the United States can be caused by various meteorological influences such as extratropical cyclones, tropical cyclones, mesoscale convective complexes, general air mass thunderstorms, upslope flow, fronts, and the North American Monsoon. Reanalyses, such as the

Section 5


presentation, a summary of our recent experience of these user requirements will be given.

The Work Package on Evaluation in the European FP7-Project UERRA (“Uncertainties in Ensembles of Regional ReAnalyses”) is focusing on the evaluation of user-relevant parameters and provides results for selected requirements from the renewable energy sector.

For example, time series of temperature and precipitation are available at sufficiently high spatial density since 1881 and can be used to derive monthly maps of these parameters which are used to provide monthly updates on the state of climate in Germany to the public (see e.g. http://www.deutscher-klimaatlas.de). However, in recent years new requirements for improved climate monitoring products came up, which cannot be fulfilled with such a traditional approach.

One important example are wind conditions at different height levels, over land but also over the North and the Baltic Sea. At these locations and heights, no long series with direct observations are available. In addition to that wind measurements from conventional stations might be affected by inhomogeneities. Improved climatologies are not only requested by the commercial sectors, but are also needed for assessments of different government agencies, e.g. for continuously assessing the progress in the transition of the energy sector or providing basic information for longer-term decisions in the energy sector.

Regional reanalysis has the potential to provide the required products, but a quality assessment of these products is a prerequisite. The applications therefore have implications on the requirements for uncertainty estimates and timeliness of the reanalysis products. In the

percentiles. Strong seasonal and spatial variability have been identified with an increase of the wind speed over the ocean and a decline over land, although disagreement between the reanalyses has been identified, particularly for the JRA-55 reanalysis which overestimates the trends over land. The causes of these wind speed trends are discussed in terms of the wind speed at 850 hPa, because although changes in land use, aerosols and the recent modifications of the large-scale circulation have been identified to play a role over wind speed trends, it is still not fully understood how these factors could affect wind speed trends at global scale.

On requirements for the application of reanalyses in the context of climate monitoring and energy applications in Germany

Author Frank Kaspar


Co-authorsA. K. Kaiser-Weiss (Deutscher Wetterdienst), M. Borsche (Deutscher Wetterdienst)

Germany’s meteorological service (Deutscher Wetterdienst) is responsible to provide regular statements on climate and climate change in Germany. Traditionally, these statements are based on the long time series of meteorological observations taken at conventional statements.

Intercomparison of the near-surface wind speed trends in three reanalyses

Author Verónica Torralba

Affiliation Barcelona Supercomputing Center (BSC)

Co-authorsF. J. Doblas-Reyes (Barcelona Supercomputing Center (BSC), Institució Catalana de Recerca i Estudis Avançats (ICREA)), N. Gonzalez-Reviriego (Barcelona Supercomputing Center (BSC)), L. Lledó (Barcelona Supercomputing Center (BSC)), R. Marcos (Barcelona Supercomputing Center (BSC)), N. Cortesi (Barcelona Supercomputing Center (BSC)) and A. Soret (Barcelona Supercomputing Center (BSC)

Wind energy users have recently incorporated reanalyses products for the evaluation of the long-term wind speed variability, particularly in those regions where there are not long observational records available. This study explores the wind speed long-term trends at global scale in the last decades (1980-2015) using three reanalyses: ERA-Interim, Japanese 55-year Reanalysis (JRA-55) and Modern Era Retrospective-Analysis for Research and Applications (MERRA-2).

The intercomparison focuses on the seasonal variability of the mean wind speed but also the 10th and 90th

Section 5


In this study, we first assess the low-frequency variations of precipitation and temperature over France in the long-term atmospheric reanalyses. Then, a new statistical approach based on the results of a statistical downscaling method applied to the reanalyses and constrained by available long-term homogenized precipitation and temperature observations over France is presented.

The reconstructed meteorological forcing and in particular the low-frequency variations are evaluated. The river flows obtained with an hydrological model forced by the reconstructed meteorological forcing are also compared to the few available long-term observed series. The added value of constraining the results of statistical downscaling with homogenized observations is then discussed. The interest of our approach to study the multidecadal variations in different variables of the continental hydrological cycle over France is finally highlighted.

Development of long-term hydro-meteorological reconstructions over France based on large scale atmospheric reanalyses to study the multi-decadal variability of French river flows

Author Rémy Bonnet

Affiliation CECI-CERFACS

Co-authorsJ. Boé (CECI-CERFACS), G.Dayon (CECI-CERFACS)

Recent studies based on the few available long-term observations show a large multidecadal variability in French river flows. Understanding the mechanisms behind this variability is a challenging issue, given the limitation of observed data-sets. The recent release of two extended large-scale atmospheric reanalyses (NOAA 20CR and ECMWF ERA20C) has opened great opportunities in that context.

They can be downscaled, here with a statistical downscaling method already used in a climate change study, to obtain the long-term high resolution meteorological forcing needed for hydrological modelling. A limitation of this approach is that the reconstructions strongly depend on the quality of the reanalyses and some studies highlighted potential unrealistic long-term trends or artificial temporal variations in long-term reanalyses.

and climate applications, and CTRIP is the river routing model used for climate applications at Météo-France.

Such a system provides not only ECVs, such as soil moisture, snow depth, etc., but also computes the various components of the water cycle: precipitation, surface runoff, soil infiltration and water storage, as well as the time evolution of rivers discharge and aquifers height. A description of the MESCAN-SURFEX-CTRIP system will be done first. A detailed analysis of the water cycle components climatology over the 50-year period over Europe will be done and comparisons with independent observations of river discharges and snow depths will be discussed.

Uncertainties will also be discussed based on simulations of a MESCAN-SURFEX-CTRIP 8-member ensemble covering the 2006-2010 period. Additional information about the UERRA project can be found at http://www.uerra.eu

The research leading to these results has received funding from the European Union, Seventh Framework Programme (FP7-SPACE-2013-1) under grant agreement no 607193.

On the use of the 50-year high-resolution UERRA re-analysis for a hydro-meteorological application over Europe

Author Patrick Le Moigne

Affiliation Météo-France

Co-authorsC. Szczypta (Météo-France), A. Verrelle (Météo-France), E. Bazile (Météo-France), R. Abida (Météo-France)

The UERRA project is a 4-year project (2014-2017) financed by the European Union under its 7th Framework Programme SPACE. One of its main objectives was to build a high resolution (5.5km) 50-year reanalysis of surface essential climate variables (ECV) over Europe, together with uncertainty estimates. The atmospheric UERRA reanalysis relies on the HARMONIE system and the ALADIN model at 11km horizontal resolution.

A downscaling at 5.5km is performed to derive wind and the downwards radiative fluxes, and to provide background fields for the MESCAN surface analysis of 2m temperature and relative humidity and 24h accumulated precipitation. These mesoscale fields are then used to drive hydro-meteorological off-line simulations based on the coupled SURFEX-CTRIP system, where SURFEX is the land surface model developed and used at Météo-France for NWP

Section 5


The circulation and hydrological stratification are compared with the results of two different ocean reanalyses: MEDRYS and MFS, the latter being the ocean reanalysis performed for the Mediterranean Sea within the framework of the Copernicus Marine Environment Monitoring Service (CMEMS). In particular MEDRYS have been performed with the same configuration of the NemoMed model and use the same forcing of the hindcast simulations. The availability of long time-series of Essential Climate Variables from ccean reanalyses is important for the validation of the hindcast run of climate models, which is mandatory in view of the use of climate models for future scenario projections.

NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis is a publicly-available high-resolution dataset (~50 km), with assimilated satellite retrievals of ozone, that characterizes stratospheric and upper-tropospheric ozone on the same spatiotemporal resolution as the meteorology. We find stratospheric intrusions which impact surface air quality are well represented in the MERRA-2 reanalysis.

This is demonstrated through a case study analysis of stratospheric intrusion events which were identified by the United States Environmental Protection Agency (EPA) to contribute to elevated ground-level ozone in spring 2012 in Colorado. The stratospheric intrusions

Mediterranean Sea circulation in high-resolution hindcast simulations and reanalyses

Author Gianmaria Sannino

Affiliation ENEA

Co-authorsA. Bargagli (ENEA), A. Carillo (ENEA), A. Dell’Aquila (ENEA), R. Iacono (ENEA), E. Napolitano (ENEA), G.Pisacane (ENEA), M.V. Struglia (ENEA), J.Beuvier (Mercator Océan)

Recent atmospheric reanalysis products, such as ERA40 and ERA-Interim, and their regional dynamical downscalings, prompted the scientific community to perform hindcast simulations of the Mediterranean Sea, giving us the opportunity to evaluate the response of ocean models to a realistic interannual air-sea fluxes atmospheric forcing. On the other hand, ocean reanalysis products represent an interesting reference dataset for the evaluation of these hindcast simulations.

The objective of this work is to present a comparison of two recent hindcast simulations of the Mediterranean Sea Circulation, performed at 1/12° horizontal resolution with different ocean models (MITgcm and NemoMed). The simulations share the same atmospheric forcing obtained by a downscaling of the ERA-Interim atmospheric reanalysis performed by the Regional Climate Model ALADIN-Climate (ALDERA).

as predictors: daily precipitation and its rolling sum, snow depth and its rolling sum, the first three modes of geopotential height at European level. We have used three distinct values for the “width” of the rolling sum: five days, 30 days and the value which maximise the correlation with the generation data.

Four different models have been used to model the daily generation of hydro-power: linear-regression model, a regression tree, an ensemble of model trees and Random Forests. Using a cross-validation procedure, all the combinations of models, countries and generation type have been tested, summarising the results using ranked correlation. The modelling performance for run-of-river is higher than the other two categories: correlation is above 0.9 for France, Germany, Romania and Norway.

More surprisingly, the correlation is above 0.7 also for water reservoir generation for countries like France, Germany, Portugal, Norway, Spain and Sweden. We can conclude that meteorological predictors, such as those from the ERA-Interim reanalysis, used as input to a purely statistical approach as that proposed in this work, are effective at modelling, and potentially predicting, hydro-power generation at country scale.

From data mining to information extraction: using ERA-Interim reanalysis to model hydro-power production in Europe

Author Matteo De Felice

Affiliation ENEA

Co-authorsL. Dubus (EDF), A. Troccoli (University of East Anglia)

The installed capacity of renewable energy sources (RES) is steadily increasing in European countries. For an efficient integration and management is important to be able to explicate the link between the meteorological variables and the generation of electricity. To this end, several approaches can be used, including data-driven methods (statistical models, machine-learning).

To successfully build a data-driven model it is fundamental the availability of high-quality data sets of observed data, i.e. generated electricity and meteorologica predictors for hydro-power modelling. Hydro-power generation data has been obtained from the ENTSO-E Transparency Portal, divided in three categories (run-of-river, water reservoir and pumped storage) and available for all the ENTSO-E countries since January 2015.

Meteorological data has been obtained from ECMWF ERA-Interim reanalysis. The following variables (averaged at country-level) have been considered

Section 5


simple dynamical downscaling of ERA 5 reanalysis data is applied through a cascade of regional atmospheric/wave models. A long-term goal of this study is to identify the long-term trends in the last 30-35 years in order to better understand the effects linked to the impact of climate change along the coast.

The methodology applied is based on:- a high resolution atmospheric model (WRF-ARW), run at a horizontal resolution of about 3 km;- a finite element wave model (WW3), able to compute high-resolution waves along the coast, at a resolution up to 300-400 meters. Our target area is the North-Western Mediterranean, characterized by a marked variability in wind/wave regimes.

The evaluation period is 3 months and the quality assessment has been performed by using regional observed data (coastal buoys and anemometers). Results show that regional downscaled data provide lower errors in the mean wave parameters and wind regimes with respect to global data and some significative improvements with respect to studies based on past reanalysis data. Moreover we present results concerning the use of the multiple members of the ERA5 data to improve the downscaled information.

Further to assessing the eddy statistics from three different datasets, a global 3D eddy detection system is implemented in order to bypass the need of regional-dependent definition of thresholds. It thus provides full three dimensional eddy structures segmenting vertical profiles from local rotational velocities. This criterion is crucial for discerning real eddies from transient surface noise. Our analysis shows that the latter impacts for about the 10% of eddy population.

Downscaling ERA-5 reanalysis data for coastal climate applications and evaluation of uncertainty of coastal data

Author Carlo Brandini

Affiliation CNR Ibimet – Consorzio LaMMA

Co-authorsValerio Capecchi (CNR-Ibimet & Consorzio LaMMA), Francesco Pasi (CNR-Ibimet & Consorzio LaMMA), Stefano Taddei (Consorzio LaMMA), Alberto Ortolani (CNR-Ibimet & Consorzio LaMMA), Bernardo Gozzini (Consorzio LaMMA).

The management of coastal zones requires precise data concerning past wind/wave regimes and future climate trends. Many studies have been based on low resolution reanalysis data that cannot allow a detailed description of the variability induced by local conditions. We present a feasibility study where a

They can largely affect the estimate of lateral turbulent fluxes of heat and tracers together with vertical exchange processes, typically occurring mostly at wavelengths less than 100km. In this work, we focus on the role of assimilative schemes in enhancing the three-dimensional variability by comparing the 3D eddy content and energetics among three different datasets: a global ocean reanalysis (C-GLORS), a free global ocean simulation (NEMO system) and an observation-based dataset (ARMOR3D) used as an independent benchmark.

Datasets are at 1/4 horizontal resolution and cover a 10-year period. While the free simulation fairly reproduces eddies emerging from western boundary currents and deep baroclinic instabilities, it underestimates shallower vortexes. The ocean Reanalysis recovers most of the missing turbulence that is not generated by the model itself and consistently projects surface variability through the full water column.

Eddies are responsible for more than 60% of total EKE in regions where deep baroclinic instabilities occur and where eddy cores are shown to be located well-below the ocean surface. Eddy thickness is also compared, ARMOR3D shows much deeper eddies compared to the Reanalysis dataset where deep currents are consistently generated by the model primitive equations thus embedding baroclinic contribution from density gradient as well as several different processes.

are identified in MERRA-2 by the folding of the dynamical tropopause under the jet stream and subsequent isentropic descent of dry, ozone-rich stratospheric air towards the surface near the location of the observed ozone air quality exceedences.

The MERRA-2 reanalysis can support air quality agencies for more rapid identification of the impact of stratospheric air on surface ozone and demonstrates that future operational analyses may aid in forecasting such events.

A three-dimensional characterisation of eddy activities in a global ocean eddy-permitting reanalysis

Author Andrea Cipollone

Affiliation CMCC

Co-authorsS. Masina (CMCC, INGV), A. Storto (CMCC), D. Iovino (CMCC)

Ocean Reanalyses, at eddy-permitting resolution, have nowadays reached a satisfactory degree of accuracy that allows for first investigations about the contribution of mesoscale variability to the ocean dynamic and energetics. Thanks to the new high-resolution satellite products, data assimilation procedures can have a remarkable impact on the ocean variability over a wide range of features that could not be well reproduced otherwise.

Section 5


Global high-resolution simulation capacity can benefit enormously next generation reanalyses products when combined with refinements in the treatment of physical processes to better account for regional and local meteorological/climate/human-induced changes.

This presentation will cover current efforts to characterise the Earth surface at kilometre-scale making use of recent remote-sensing dataset in collaboration with the Copernicus Services and it will illustrate some of the challenges with the internal consistency across datasets and with their use in long reanalysis.

A roadmap to Earth surface kilometre-scale simulations

Author Gianpaolo Balsamo

Affiliation ECMWF

Co-authorsG. Arduini, A. Beljaars, S. Boussetta, M. Choulga, E. Dutra, H. Herschbach, J. Munoz-Sabater, P. de Rosnay, I. Sandu, N. Wedi (ECMWF)

The strive to produce increasingly more accurate forecasts has pushed horizontal resolutions of global Earth System Models (ESM) to break into single-digit kilometre-scale (e.g. 9 km for global HRES forecasts at ECMWF with a vision to increase it further towards 2025), while many National Meteo-Hydrological Services already run at 1-2 km resolution on wide regional domains. At about 1km there is close to a billion grid points covering the Earth surface involving the use of High Performance Computing to be timely simulated.

However, there are not only computing and software challenges involved, as accuracy requires to be able to characterise the surface ancillary conditions at those resolution (vegetation and soil, water-land-snow-ice fractions, and any meteorologically relevant properties) therefore involving satellite remote sensing observations and optimisation/inversion algorithms to estimate non-observable quantities.

Section 5


PostersPosters


Section 1 – Status and plans of reanalysis productions

A 50 year surface analysis over Europe at 5.5km within the UERRA project

Author Eric Bazile

Affiliation Météo-France/CNRS

Co-authorsR. Abida, C. Szczypta, A. Verrelle, P. Le Moigne, C. Soci (1) (Météo-France CNRS) (1) ECMWF

The UERRA project is a 4-year project (2014-2017) financed by the European Union under its 7th Framework Programme SPACE. One of its main objectives is to provide a 50-year reanalysis dataset of surface Essential Climate Variables (ECV) at 5.5km grid at European scale, together with, as much as possible, uncertainty estimates.

The system used to provide the ECV and consistent other surface variables at 5.5km such as soil moisture at several levels, surface evaporation, snow depth is based on a surface analysis (MESCAN) for 24h accumulated precipitation (RR), 2m temperature (T2m) and relative humidity (rh2m) and on the surface platform called SURFEX. The atmospheric re-analysis done by SMHI with the HARMONIE system and the ALADIN model at 11Km is used to

provide the background fields at 5.5km for the surface analysis (T2m, Rh2m, RR) and to downscale the downward radiative fluxes and the wind at 5.5km required to drive SURFEX with the T2m, Rh2m and precipitation analysis.

A Conventional Enkf atmospheric REanalysis (CORe)

Author Wesley Ebisuzaki

Affiliation CPC/NWS/NOAA

Co-authorsA. Kumar (NOAA-CPC), J. Whitaker (NOAA-PSD), J. Woollen (NOAA-EMC), H-C Lee (NOAA-CPC), L. Zhang (NOAA-CPC)

Atmospheric reanalyses can be optimized to produce the most accurate analyses by assimilating all observations including satellite observations. However, this type of reanalysis often shows discontinuities in various time series with the introduction of new satellite systems. An atmospheric reanalysis can also be optimized for a more consistent time series by limiting the observations to a more temporally consistent set of observations.

This was the approach used by the 20th Century Reanalysis (Campo et al 2011) which only assimilated the surface pressure observations. The trade off for the consistency was a less accurate reanalysis because fewer observations were assimilated. The Climate Prediction Center (CPC, NWS/NOAA) requires a modern reanalysis to replace the

venerable NCEP/NCAR Reanalysis (R1). This new reanalysis would be between these two extremes.

The accuracy would have to be similar or better then R1 without the gross artifacts from the introduction of the various satellites. The reanalysis would also have to span the 1950’s to the present. Towards this goal, we considered whether improvements in data assimilation and modeling would allow a modern system that assimilated conventional observations to have similar or better accuracy than the old R1 which assimilated satellite data using vertical temperature retrievals. We ran an experimental reanalysis using an Ensemble Kalman Filter, atmospheric data assimilation system (Jeff Whitaker, Climate Diagnostics and Predication Workshop, Orono, Maine, 2016). This system used a T254 64 vertical-level semi-Lagrangian version of the GFS (Global Forecast System) model.

The system assimilated conventional observations, cloud-track winds and GPS-RO (COSMIC data). The last two items use satellite data but are relatively insensitive to the biases in the radiance measurements. We created an experimental reanalysis that spans 1950 to 2010. Using ERA-interim as a proxy for truth, we found that the CORe reanalysis was usually closer to ERA-interim than R1 suggesting CORe met the accuracy requirement in the troposphere and lower stratosphere.

The accuracy was better near regions with more observations such as the Northern Hemisphere and closer to the surface. We did not find artifacts related to the introduction of new satellites as CORe did not assimilate radiances from the satellites. However, we did encounter some other discontinuity issues that may be related to stream boundaries and to the prescribed SST analyses. We will show comparisons with other reanalyses.

Aerosols in MERRA-2 and Plans for Aerosols in Future GMAO Reanalyses

Author Arlindo M. da Silva

Affiliation NASA/Goddard Space Flight Center

Co-authorsV. Buchard (NASA/GSFC, USRA), C. Randles (Exxon Mobile), A. Darmenov (NASA/GSFC)

MERRA-2 is NASA’s latest reanalysis for the satellite era (1980-present) using Version 5 of thr GEOS Earth System model. This project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales, and includes interactive aerosols for the entire period. As another step towards an integrated Earth System Analysis (IESA), MERRA-2 includes for the first time aerosols in a reanalysis for the satellite era, improves the representation of stratospheric ozone, and better characterizes cryospheric


Creating a sea ice reanalysis using an ocean model forced by surface fields from atmospheric reanalyses

Author Thomas Collow

Affiliation INNOVIM, LLC/NOAA Climate Prediction Center

Co-authorsWanqiu Wang (NOAA Climate Prediction Center), Arun Kumar (NOAA Climate Prediction Center)

A new Arctic sea ice reanalysis product is being developed at the NOAA Climate Prediction Center (CPC), which will be used to initialize sea ice forecasts. Experimental Arctic sea ice outlooks have been produced at CPC since 2015 using sea ice thickness initialization data from the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). Our plan is to replace PIOMAS with a new product that is consistent with the forecast model used (Climate Forecast System version 2).

To develop this new product, experiments have been conducted with the Geophysical Fluid Dynamics Laboratory Modular Ocean Model version 5 (MOM5). Here we will present results from these experiments, highlighting the impacts of using different surface boundary conditions, namely from the Climate Forecast System Reanalysis (CFSR) and Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2).

(HErZ). The HErZ branch on climate monitoring is a research group located at University of Bonn and University of Cologne, funded by DWD. The aim is to analyze the potential of the regional reanalysis system as a tool for climate monitoring of DWD. (2) Within the EU-funded project UERRA an approach for an COSMO ensemble reanalysis was developed.

Within that project, a dataset with 12 km resolution is currently produced and will be compared to regional reanalyses of other European partners. Both activities have a strong focus on the evaluation of the datasets. There is strong interest in the datasets from various sectors, especially the energy sector. Therefore, one focus of the evaluation activities are parameters that are relevant for such applications.

In this presentation we will provide an overview of the reanalysis system, the datasets, evaluation results with focus on the user-relevant parameters and ongoing activities. Further details on specific evaluation activities will be addressed in separate presentations.

An overview on regional reanalysis activities based on the COSMO model

Author Frank Kaspar


Co-authorsS. Wahl (Hans-Ertel-Centre for Weather Research, University of Bonn), J. Keller (Hans-Ertel-Centre for Weather Research, University of Bonn, Deutscher Wetterdienst), M. Borsche (Deutscher Wetterdienst), M. Lockhoff (Hans-Ertel-Centre for Weather Research, University of Bonn), A. K. Kaiser-Weiss (Deutscher Wetterdienst), D. Niermann (Deutscher Wetterdienst), A. Hense (Hans-Ertel-Centre for Weather Research, University of Bonn), S. Crewell (Hans-Ertel-Centre for Weather Research, Unversity of Cologne)

The COSMO model (Consortium for Small-scale Modeling) is a non-hydrostatic limited-area atmospheric model, that is used for operational and for research applications by Germany’s Meteorological Service (Deutscher Wetterdienst, DWD) and other members of the consortium (see http://www.cosmo-model.org/).

The model was also used to generate a set of regional reanalysis datasets within two activities: (1) A 6km deterministic reanalysis for the European CORDEX-domain and a 2 km reanalysis for Central Europe was produced within the Hans-Ertel-Centre for Weather Research

processes. In this talk we will present results relating to the introduction of aerosols in MERRA-2.

The assimilation of Aerosol Optical Depth (AOD) in GEOS-5 involves very careful cloud screening and homogenization of the observing system by means of a Neural Net scheme that translates MODIS and AVHRR radiances into AERONET calibrated AOD. The system also assimilates MISR and AERONET AOD observations.

These measurements are further quality controlled using an adaptive buddy check scheme, and assimilated using the Local Displacement Ensemble (LDE) methodology.

We will present a summary of our efforts to validate the MERRA-2 aerosols. The GEOS-5 assimilated aerosol fields are first validated by comparison to independent in-situ measurements (PM2.5 concentrations, long term surface dust concentrations, Maritime Aerosol Network, airborne and ground based lidars, UV based measurements, etc.) We will conclude with a discussion of our plans to extend the historical aerosol observing system in future GMAO reanalyses.

Section 1


that is planned to be continued in Near-Real-Time through the C3S operational service.

It is also expected that in a second phase of production this dataset will be back extended to the year 1950. ERA5-Land will be the result of a single simulation driven by near-surface atmospheric fields from ERA5 atmospheric reanalysis and climatic fields at native resolution. Additionally, near surface temperature and humidity fields will be adjusted using daily computed environmental lapse-rates.

One of the added values of ERA5-Land with respect to the ERA5 atmospheric reanalysis is a global projected horizontal resolution of approximately 9 km (around 4 times finer resolution than ERA5), matching the current operational ECMWF TCo1279 operational grid, and therefore providing consistent input for Numerical Weather Prediction and climate studies involving land water resources, but also for downstream applications such as those based on hydrological and agricultural modeling.

ERA5-Land will also include, for the first time, an estimation of key land-variables uncertainty based on meteorological forcing and model parameters uncertainties supplied by a 10-member ensemble parallel run, hence providing vital information to land-surface data assimilation systems. The offline nature of land reanalysis allows to incorporate forefront model developments before the production phase.

the scope and usability of the ECCO Central Estimate will be expanded in support of the broader climate change science community, for instance, by the development of an open source adjoint of the ocean model, valuable for diverse applications. These products and future plans for the ECCO Central Estimate will be discussed.

ERA5-Land: a new state-of-the-art global land surface reanalysis dataset

Author Joaquin Munoz Sabater

Affiliation ECMWF

Co-authorsE. Dutra (Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa), G. Balsamo (ECMWF, Reading, UK), S. Hirahara (Global Environment and Marine Department, Japan Meteorological Agency), H. Herbasch (ECMWF, Reading, UK), S. Boussetta (ECMWF, Reading, UK), C. Albergel (CNRM, Météo-France), D. Dee (ECMWF, Reading, UK)

The European Centre for Medium Range Weather Forecasts (ECMWF) is implementing, on behalf of the European Commission, the Copernicus Climate Change Service (C3S, http://climate.copernicus.eu/). Among its portfolio of product, C3S is developing the ERA5-Land dataset, a new, state-of-the-art, high-resolution, global, hourly land-surface dedicated reanalysis dataset from 1979 (beginning of the satellite era)

kinematical consistency, allowing for instance for budget closures in terms of explicit physical processes, and making amenable investigations of attribution and causation of the oceanic state.

This presentation describes the status and plan of ECCO’s flagship product, the Central Estimate. “ECCO Version 4” represents the Consortium’s ongoing Central Estimate. First established in 2015, Version 4 is of moderate spatial resolution (40-100km) but with a domain that is truly global, including the Arctic Ocean. Recent enhancements include use of new observations (e.g., GRACE ocean bottom pressure and Aquarius sea surface salinity), model improvements (e.g., geothermal heating, sea ice model), and additional controls in the estimation (e.g., mixing coefficients, correlated uncertainties), that result in a more complete and accurate estimate than before.

Efforts are underway to further advance the Central Estimate to study Earth’s climate with a focus on improving understanding and prediction of global and regional sea level variability and change. The new initiative, called “ECCO-Sea Level”, will incorporate capabilities for coupled ocean and ice sheet estimation to improve the estimate’s representation of ocean-ice interaction pertinent to sea level rise.

The estimation’s spatial resolution will also be refined to eddy-permitting scales to better resolve the energetic variations of the circulation. Simultaneously,

Also shown will be the impacts of using different vertical resolutions for the top layer of the ocean (10m and 1m), as well as the impacts of different sea surface temperature restoring datasets, including those from the National Climatic Data Center (NCDC) and the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Finally, we will share results from the assimilation of sea ice concentration observations from the NASA Team dataset into the model.

ECCO-Sea Level: The next phase in the “Estimating the Circulation and Climate of the Ocean” Project

Author Ichiro Fukumori

Affiliation JPL/Caltech

Co-authorsP. Heimbach (Univ. Texas Austin), C. Hill (MIT), D. Menemenlis (JPL/Caltech), R. M. Ponte (AER)

The “Estimating the Circulation and Climate of the Ocean” (ECCO) Consortium has pioneered in the advancement of ocean state estimation. The ECCO estimates combine nearly all extant observations of the ocean with a state-of-the-art ocean general circulation model spanning the globe, by adjusting its atmospheric forcing and other independent controls, over the modern observational era from the beginning of continuous satellite altimetry measurements in the early 1990s to the present. The estimates are characterized by their dynamical and

Section 1


Land Surface Reanalysis in the CMA 40-year Reanalysis

Author Xiao Liang

Affiliation CMA

Co-authorsLipeng Jiang (Affilation 2), Chunxiang Shi (Affilation 3), Zhiquan Liu (Affilation 4)

The land surface interacts with weather and climate through regulation of the water and energy fluxes at the land-atmosphere interface. For example, soil moisture is important for the partitioning of the surface energy between latent, sensible and soil heat fluxes, and hence affects the soil temperature and subsequently the near-surface air temperature. The development of land surface reanalysis methods and long-time-series land data products is critical for improving weather and climate forecasts.

The presentation will discuss current developments and future plans of the CRA-40/land reanalysis, which is a supplemental land surface reanalysis system and data product of the CMA 40-year Reanalysis (CRA-40), generated at the China Meteorological Administration. CRA-40 is initiated in 2014, which aims to construct the China’s first global atmospheric reanalysis system and produce a long-time-series product since 1979.

The comparison between the two SST assimilation strategies shows that both direct assimilation and nudging scheme have their advantages and disadvantages and a combination of these two schemes is desirable in future work.

Finally, the uncertainty of the reanalyses heat content due to the different atmospheric forcing is assessed by comparing the root mean square difference (RMSD) between pair of experiments that share the same assimilation configuration but are forced by different atmospheric reanalyses.

It turns out that the upper ocean (top 700m) heat content RMSD when in-situ profiles are assimilated is significantly smaller than the control experiments RMSD even during the first half of the XX century, meaning that even a poor observing network is able to reduce the atmospheric forcing uncertainty. Conversely, the total column heat content remains unconstrained with respect to the atmospheric forcing uncertainty until the mid 1950s.

monthly HadISST reconstructed fields. Both reanalysis systems are forced by the NOAA/CIRES 20th Century Reanalysis version 2 (20CRv2) and the ECMWF ERA-20C, thus forming an ensemble of four realizations, plus control experiments.

Due to large biases at high latitudes, corrections are applied to the 20CRv2 atmospheric forcing, based on the comparison with ERA-Interim during the overlapped period. The reanalyses are designed to investigate the impact of different strategies for constraining the SST in long-term assimilation experiments, the feasibility of assimilating subsurface observations in the same kind of experiments, and the impact of the atmospheric forcing. In general, these ocean reanalyses are able to capture trends and variability of some key ocean parameters.

A warm bias of SST with 20CRv2 in the first half of the century leads to incorrect long-term trends, even though SST anomalies are realistically captured. Heat contents at 0-300m, 0-700m and 0-2000m have an increasing trend in all experiments, consistent with available observation-based products (NODC heat content dataset) during the second half of the century. In order to reproduce realistic mass transport, mixed layer depth and eddy kinetic energy, it is necessary to assimilate vertical profile data, although this leads to some discontinuities in the reanalysis time series.

For example, ERA5-Land could benefit from a larger discretization of the soil layer permitting better propagation of the energy and water fluxes through the vertical dimension of the soil layer (currently under development). This paper presents the methodology that will be used to produce the ERA5-Land dataset, as well as its main strengths and weaknesses.

First results obtained from demonstrative scout-runs will be shown and discussed, and their performance will be assessed by comparison to in-situ data and other long-term available datasets.

Historical ocean reanalyses (1900-2010) using different data assimilation strategies and atmospheric forcing

Author Chunxue Yang

Affiliation ISAC-CNR

Co-authorsSimona Masina (The Euro-Mediterranean Center on Climate Change, Bologna, Italy ) and Andrea Storto (The Euro-Mediterranean Center on Climate Change, Bologna, Italy)

A set of historical ocean reanalyses covering the period from 1900 to 2010 are performed and analysed. All the reanalyses assimilate vertical profile observations with a 3D-Var assimilation scheme but differ in the way they use SST data, which are either assimilated ICOADS observations or nudged to

Section 1


analysis of surface parameters including screen level temperature, 10m wind speeds, mean sea-level pressure (MSLP), soil temperatures, soil moisture and 24 h rainfall accumulations. The quality of the 3-D variational data assimilation used in the reanalysis is also assessed. Preliminary analysis shows that it takes almost 12 months to spin up the deep soil in terms of moisture, justifying the choice of running year-long spin up periods.

Overall, the model performed consistently over the time period. Small biases were found in screen-level temperatures, MSLP and 10m wind speed. Soil temperatures are well represented by the model. 24 h accumulations of precipitation generally exhibit a small positive bias of 1mm per day and negative biases over mountains due to a mismatch between the model orography and the geography of the region. MÉRA outperforms the ERA-Interim reanalysis, particularly in terms of standard deviations in screen-level temperatures and surface winds. This dataset is the first of its kind for Ireland and is now publically available.

the horizontal resolution of about 30km and the time frequency of 6 hours.

The products especially the estimates of soil moisture, ground temperature and soil temperature are assessed by comparing with a large number of ground-based observations. Compared with other land surface reanalysis products, the hallmark of CRA-40/land is the use of much more observed precipitation in China to drive the land surface model. CRA-40/land has not yet benefit from the assimilation of land surface observations. The advantages, challenges and future plans of assimilation observations into the system will be discussed in the presentation.

Met Éireann high resolution reanalysis for Ireland

Author Emily Gleeson

Affiliation Met Éireann

Co-authorsE. Whelan (Research, Environment and Applications Division, Met Éireann, Dublin, Ireland), J. Hanley (Research, Environment and Applications Division, Met Éireann, Dublin, Ireland)

The Irish Meteorological Service, Met Éireann, has carried out a 35-year very high resolution (2.5 km horizontal grid) regional climate reanalysis for Ireland using the ALADIN-HIRLAM numerical weather prediction system. Here we provide an overview of the reanalysis, called MÉRA, as well as a preliminary

Earth system concept of CERA-20C, by accounting for the full observing system and by including land data assimilation.

In CERA-SAT the land-atmosphere data assimilation is weakly coupled, using a coupled land-atmosphere background forecast and separate analyses for the atmosphere and for the surface (screen level variables, soil moisture and snow). Conventional and satellite observations that inform on the state of both subsystems are assimilated.

They are located at the land-atmosphere interface and include two-meter temperature and relative humidity, snow depth, and soil moisture. In this poster we present the land-atmosphere weakly coupled assimilation approach used in CERA-SAT.

Perspectives of coupling enhancement using EDA-based (Ensemble Data Assimilation based) cross correlation estimates and land-atmosphere coupling at the outer loop level with 4D-Var are discussed as perspective for future generation of coupled reanalyses.

CRA-40/land is an off-line subsystem of CRA-40, which is designed to provide land surface components such as ground temperature, soil moisture, snow, etc. CRA-40/land system is constructed based on the LIS (Land Information System) which is developed primarily by NASA and has been used in CFSR-land reanalysis. A 10-year CRA-40/land experimental product is produced with

Land-atmosphere weakly coupled assimilation in CERA-SAT

Author Patricia de Rosnay

Affiliation ECMWF

Co-authorsD. Schepers (ECMWF), P. Dahlgren (ECMWF)

The CERA-SAT coupled climate reanalysis for the satellite era (see presentation by Schepers et al.) is a key product of the ERA-CLIM2 European project. It relies on an Earth System approach focusing on atmosphere, ocean, waves, land, and sea ice. In CERA-SAT different data assimilation methods are used for the each component of the Earth System.

A hybrid four-dimensional variational data assimilation (4D-Var) is used for the atmosphere, a 3D-Var with the first guess at appropriate time (FGAT) is used for the ocean analysis, and a combination of Optimal Interpolation (OI) and simplified Extended Kalman Filter (EKF) are used for the land surface.

CERA-SAT relies on a pioneering coupled ocean–atmosphere data assimilation approach (as does CERA-20C, the coupled climate reanalyses of the 20th century, see presentation by Laloyaux et al.), with the ocean 3D-Var coupled to the atmospheric 4D-Var at its outer loop level. CERA-SAT also extends the

Section 1


The model component is the NEMO platform driven at the surface by ECMWF ERA-Interim reanalysis. Observations are assimilated by means of a reduced-order Kalman filter with a 3D multivariate modal decomposition of the background error.

Performance and quality assessment of the global ocean eddy-permitting physical reanalysis GLORYS2V4.

Author Gilles Garric


Co-authorsL. Parent (Mercator Océan), E. Greiner (CLS), M. Drévillon (Mercator Océan), M. Hamon (Mercator Océan), J.M. Lellouche (Mercator Océan), C. Régnier (Mercator Océan), C. Desportes (Mercator Océan), O. Le Galloudec (Mercator Océan), C. Bricaud (Mercator Océan), Y. Drillet (Mercator Océan), F. Hernandez (Mercator Océan), C. Dubois (Mercator Océan) and P-Y. Le Traon (Mercator Océan)

The last upgrade of global ocean reanalysis GLORYS2V4 produced at Mercator Océan that covers the altimetry era (1993-2016) has been performed in the framework of Copernicus Marine Environment Monitoring Service (CMEMS; http://marine.copernicus.eu/). The reanalysis is run at eddy-permitting resolution (1/4° horizontal resolution and 75 vertical levels) with the NEMO model and driven at the surface by ERA-Interim reanalysis.

Performance and quality assessment of the Copernicus Marine Service global ocean eddy-resolving physical reanalysis GLORYS12V1

Author Jean-Michel Lellouche


Co-authorsO. Le Galloudec (Mercator Océan), E. Greiner (CLS), G. Garric (Mercator Océan), C. Regnier (Mercator Océan), M. Drevillon (Mercator Océan), R. Bourdalle-Badie (Mercator Océan), C. Bricaud (Mercator Océan), Y. Drillet (Mercator Océan), P.-Y. Le Traon (Mercator Océan)

Over the past years, Mercator Océan has been regularly upgrading its global ocean physical reanalysis through improvements in the ocean model, assimilation scheme and assimilated data sets. The last upgrade concerned the eddy-permitting reanalysis GLORYS2V4 (1/4° horizontal resolution and 75 vertical levels) covering the altimetry era (1993-2016). R&D activities have been conducted at Mercator Océan in 2016/2017 in order to propose, in the framework of Copernicus Marine Environment Monitoring Service (CMEMS), an eddy-resolving physical reanalysis called GLORYS12V1, covering the same time period and based on the current real-time global forecasting CMEMS system (1/12° horizontal resolution and 50 vertical levels).

reproduced the variability of ocean and biogeochemical parameters in important dynamic processes (e.g. the inflow process). However, it was found that the model simulation yielded obvious biases, especially in the deep layers.

As expected, the assimilation has been found to impart significant positive impact in both the physical and biogeochemical simulations. For example, with the comparison with observations, the oxygen, nutrients, temperature and salinity biases in reanalysis at the Baltic proper has been significantly reduced relative to reference run. Furthermore, the reanalyzed hypoxia in the Baltic Sea is closer to the observed one relative to the reference run.

The results denoted that as a consistent reanalysis of physical and biogeochemical in the Baltic Sea and North Sea, the output data set of this reanalysis can inform the management of the North Sea and Baltic Sea ecosystem. For exampling the analysis or prediction of the trend and reason of oxygen deficiency potentially threatening.

Multi-year consistent reanalysis of physical and biogeochemical variables in the North Sea and Baltic Sea

Author Ye Liu

Affiliation SMHI

Co-authorsLars Axell (Swedish Meteorological and Hydrological Institute)

A multi-year physical and biogeochemical reanalysis was carried out in the Baltic Sea and North Sea. The model system is based on the Swedish coastal and ocean biogeochemical model (SCOBI) coupled to the NEMO-Nordic circulation model (Hordoir et al., 2015). A weak coupled data assimilation system based on a sequential ensemble interpolation kalman filter (SEIK) was adopted to merge the information of model and observations.

The high resolution remote sensing sea surface temperature, salinity and temperature profiles, oxygen and nutrient profiles observations were assimilated into the NEMO-SCOBI. The observation errors were decreased with increasing the water depth. In order to produce dynamic consistent analysis, both physical and biogeochemical observations were assimilated in the same time.

Based on the numerical experiment with and without data assimilation, the inter-comparison was implemented to validate the reanalysis results. The model has

Section 1


Status of ERA5 Reanalysis Operational Production at ECMWF

Author Raluca Radu

Affiliation ECMWF

Co-authorsP. Berrisford (ECMWF), A. Bonet (ECMWF), H. Hersbach (ECMWF), J. Hodkinson (ECMWF), A. Horanyi (ECMWF), C. Soci (ECMWF) and M. Suttie (ECMWF)

The ERA5 Reanalysis, the successor of ERA-Interim Reanalysis, is a state-of-the-art reanalysis covering the satellite era (1950 – present). It is currently produced at ECMWF in the framework of the Copernicus Climate Change Service (C3S). ERA5 is the first reanalysis to be produced operationally as a service, rather than as a research project. With respect to its predecessors, ERA5 benefits from various improvements in the data assimilation, model and observing systems from recent years. For the historical period production is divided into parallel streams, each spanning a period of 10 years, while for the present time ERA5 is produced daily near to real time (NRT).

Each stream comprises a lower resolution 10 member 4D-Var ensemble (EDA) providing flow-dependent background error information to the high resolution (HRES) deterministic assimilation cycle. The overview of the production system and the current status

will allow the representation of deep convection and temporal resolution will be sufficient to resolve the diurnal cycle. The dataset will cover the period 1979-2016. Specific tests will be undertaken in order to compare a subset of SPHERA archive with the high-resolution observative analysis derived from the regional networks over Italy (e.g. ERACLITO Antolini et al. 2015, ARCIS Pavan et al. 2013, EURO4M-APGD Isotta et al. 2014).

The project aims at having a high resolution, space and time consistent, monitoring of past decades climate over Italy and its surrounding Seas at the same time for climatic assessments (trend along the past years, climate reference for COSMO applications in different scenarios associated to Climate Change over Italy) and for feeding downstream high-resolution model applications. The project is expected to be accomplished within the end of 2019

SPHERA (High Resolution REAnalysis over Italy): plan and setup

Author Ines Cerenzia

Affiliation ARPAE-Emilia Romagna

Co-authorTiziana Paccagnella (ARPAE-Emilia Romagna)

In a framework of developing interest of EU Community towards high resolution regional reanalysis, ARPAE-SIMC proposes the development of SPHERA (High Resolution REAnalysis over Italy), the first dynamical downscaling reanalysis of the atmosphere centred over Italy with a horizontal resolution of 2.2km and a high frequency.

The Italian reference NWP model for operational limited area forecast, i.e. the COSMO (Consortium for small scale modelling) model will be applied to perform the dynamical downscaling.

This effort will complement the activity of the DWD, Deutscher Wetterdienst, and of the University of Bonn on the same field, since the initial and boundary conditions will be based on the COSMO-REA6 reanalysis archive (Bollmeyer et al. 2015), a 6 km-resolution reanalysis project covering the CORDEX european domain that is currently in production.

The assimilation of the upper air and surface conventional observations will be performed by using the continuous nudging technique. Horizontal resolution

The reanalysis system uses a multi-data and multivariate reduced order Kalman filter based on the singular extended evolutive Kalman (SEEK) filter formulation together with a 3D-VAR large scale bias correction. The assimilated observations are along-track satellite altimetry, sea surface temperature, sea ice concentration and in-situ profiles of temperature and salinity from CORA data base.

With respect to the previous version, GLORYS2V4 contains the following main improvements: a) a new initial temperature and salinity conditions derived from EN4.1.1 data base and better balanced with altimetry, b) the use of the updated delayed mode CORA4.1 in situ observations from CMEMS, c) a better observation operator in the assimilation scheme for altimetry observations d) a new hybrid Mean Dynamical Topography (MDT) referenced over the 1993-2013 period, e) an updated correction of large scale atmospheric surface precipitations fluxes and f) an update of the global climatological runoff data base together with a better account of freshwater fluxes from polar ice sheet’s glaciers.

The new reanalysis outperforms the previous version in many aspects and the presentation will give an overview of main results. The new altimetry and water masses equilibrium in the system particularly improves the representation of global thermo-haline content with a trend of +3.56 mm/year for Global Mean Sea Level together with a +1.8 mm/year for the thermo-steric signal.

Section 1


Towards a high-resolution probabilistic regional reanalysis system based on a local ensemble transform Kalman filter

Author Thomas Roesch


Co-authorsLilo Bach (DWD), Roland Potthast (DWD), Frank Kaspar (DWD), Jan Keller (DWD, Uni Bonn)

The question of high-impact weather and its relation to climate change today is of tremendous importance for all parts of our modern world. It touches all basic layers of a modern society, from logistics and production to national safety,from renewable energy political strategy and daily energy supply to personal holiday planning. National weather services and research institutions are reacting to the increasing need to estimate risk and distributions of both standard variables of weather and climate such as temperatures or humidity and high-impact phenomena such as strong precipitation, wind gusts and storms, tornados, hurricanes or fog.

The agenda of weather and climate forecasting and projection today includes the development and operation of ensemble forecasting systems (EPS) on all scales, which have the ability to model and describe the distribution of possible

Re-analysis ensemble product (GREP). The current version of this re-analysis centres around the NERC/Met Office Joint Ocean Modelling Programme (JOMP) Global Ocean 5.0 (GO5.0) and the NERC/Met Office Joint Sea Ice Modelling Programme (JSIMP) Global Sea Ice version 6 (GSI6).

A planned update to an improved version GO6/GSI8 version is expected within the next calendar year. The new version, based on NEMO vn3.6 and CICE 5.1 will include a variable volume level scheme for the ocean, a parameterisation for under-ice-shelf melt, pronostic icebergs, and a multi-layer sea ice thermodynamic scheme along with an improved representation of melt-ponds. We will show some initial results from this latest configuration, contrasting and comparing the advancements over previous versions in terms of several ocean and sea ice monitoring indicators such as heat and salt content, surface currents, sea ice volume, along with root mean square errors with the ingested observations. Additionally, recent advancements towards the assimilation of sea ice thickness to satellite observations will be presented. Our current systems only assimilate sea ice concentration, allowing model physics to integrate the thickness properties of the sea ice. This has been shown to depend on the external forcing applied to the model, and has lead to inconsistencies between the Met Office real time sea ice analysis and re-analysis. Assimilation of the sea ice will create better consistency, along with a better sea ice thickness climatology.

and sea ice data assimilation; updated forcing and observation datasets; and implementation of a generic perturbation scheme that accounts for representativeness errors from observation and structure and analysis errors from surface forcing fluxes.

The operational implementation of real-time extension of ORAS5 is also discussed; this provides ocean and sea-ice initial conditions for the ECMWF’s coupled ensemble forecasting system (spanning the medium range, monthly and seasonal forecasts ranges). Results from evaluation of ORAS5 with observed data, e.g. using RAPID-derived transport and re-processed sea-level data are also discussed, with the focus on some prominent climate signals.

The GloSea/FOAM ocean and sea ice re-analysis: Current status and future plans

Author K. Andrew Peterson


Co-authorsC. MacLachlan (Met Office), C. Harris (Met Office), A. Aguiar (Met Office), M.J. Martin (Met Office), E. Blockley (Met Office)

As part of the seasonal forecast system at the Met Office, a 1/4 degree ocean and sea ice analysis is performed for 1990 to near real time. This analysis is one of 4 members of the Copernicus Marine Environment Monitoring Service Global

of the operational production, which started in 2016, will be presented. The results are continuously monitored using a system of diagnostic and monitoring tools. Currently, the ERA5 Reanalysis dataset is partially available and will provide a large number of essential climate variables within the C3S climate data store (CDS).

The ECMWF ocean-sea ice reanalysis system ORAS5 and operational ocean analysis

Author Hao Zuo

Affiliation ECMWF

Co-authorsM. A. Balmaseda (ECMWF), K. Mogensen (ECMWF), S. Tietsche (ECMWF), P. de Rosnay (ECMWF)

A new operational Ocean ReAnalysis System 5 (ORAS5) has been implemented at ECMWF. It spans the period 1979 to present and was produced using NEMO Ocean Model coupled to LIM2 sea ice model. Subsurface in-situ observations from EN4, SLA from AVISO DUACS2014, SST from HadSST2/OSTIA and Sea Ice Concentration from OSTIA were assimilated in ORAS5 using NEMOVAR Ocean data assimilation system (in 3DVar FGAT approach).

Here we describe the most important system upgrades in ORAS5, including increase of model resolution; change to a coupled ocean-sea ice model

Section 1


at about 30 km. This gives much more detail in precipitation, temperature and wind near the surface.

The system is very efficient and parallel 10 year streams were run with 4 months spin up periods. The output data, including observation statistics, are stored on ECFS at ECMWF but the fields have been archived in the common UERRA MARS archive. The reanalysis will be presented and compared to the ERA reanalyses together with the different data types stored, as well as observation usage and diagnostics using a partly newly developed observation monitoring system.

UERRA SMHI HARMONIE-ALADIN high resolution Regional Reanalysis over Europe for 1961-2015

Author Per Undén

Affiliation SMHI

Co-authorsMartin Ridal (SMHI), Esbjörn Olsson (SMHI), Jelena Bojarova (SMHI), Klaus Zimmermann (SMHI), Heiner Körnich (SMHI) and Eric Bazile (Météo-France)

SMHI is coordinating the FP7 Project UERRA (Uncertainties in Ensembles of Regional ReAnalyses) which has developed three full upper air Regional European Reanalysis systems and two 2-dimensional ones. The project is now in its final phase and all data is archived in an openly available UERRA archive with common parameters within MARS at ECMWF.

At SMHI historical data assimilation and forecast cycles have been produced for the period 1961 until 2015 using the HARMONIE-ALADIN system. It has been run at 11 km horizontal resolution with conventional observations and a large scale constraint that adapts large scales to the global driving ERA reanalyses. ERA40 and ERA-Interim reanalyses exist during this period and provide boundary forcing. The horizontal grid resolution in UERRA of about 11 km is much higher than the global ERA analyses at 125 or 78 km respectively or even the current ERA5

events and as such the variability of extreme weather, its variables and phenomena.

We describe the setup of the ensemble data assimilation (EDA) and forecasting systems which have been developed at DWD, including the ICON global model with its hybrid ensemble variational data assimilation (EnVAR) and the ensemble prediction system ICON-EPS as well as the high-resolution ensemble data assimilation system COSMO-KENDA (Kilometer Scale Ensemble Data Assimilation).

The latter is the operational system of DWD and used by further members of the COSMO consortium. It drives the high-resolution ensemble forecasting system COSMO-DE-EPS. We demonstrate the high quality of the system.

We will then give perspectives on the use of the coupled ICON-EPS COSMO-EPS ensemble system for the investigation of climate variability for reanalysis and climate projection, which is under investigation by DWD core teams in collaboration with the Hans-Ertel center HErZ in Bonn.

Section 1


in June the Arctic albedo of the Canadian coast has slightly increased since 2008/2009.

The maximum increase of the June albedo during 1982/1983 – 2014/2015 is 0.55 and the maximum decrease is -0.51. During 2008/2009 – 2014/2015 the corresponding increase for albedo in August is 0.30 and the decrease -0.40.

Assessing the impact of GPS radio occultation measurements in ERA5

Author Sean B. Healy

Affiliation ECMWF

Co-authorsA Horanyi (ECMWF), A J Simmons (ECMWF)

GPS radio occultation (GPS-RO) measurements are now a key observation type forclimate reanalyses. They can be assimilated without bias correction, and they perform the role of “nchor measurements” in variational radiance bias correction schemes. The measurements provide accurate temperature informationin the upper troposphere and lower/middle stratosphere.

Furthermore, they have improved the consistency between stratospheric temperature reanalyses since 2007, when GPS-RO numbers increased with the introduction of COSMIC data. In this talk we review the measurement

means of the Satellite Application Facility on Climate Monitoring (CM SAF, funded by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)) data record CLARA-A2 SAL (CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data – Edition 2, surface albedo), which covers the years from 1982 to 2015, in the resolution of 0.25° (global product). The SAL albedo contains contributions both from the sea ice and the open ocean. The previous CLARA-A1-SAL release already showed a dramatic decrease in the surface albedo of the Arctic sea ice area during 1982-2009. Variations in mean sea-ice albedo could be explained using sea-ice concentration, surface air temperature and elapsed time from onset of melt as drivers.

The CLARA-A2 SAL data set shows a continuation of the albedo decrease in the Siberian and Scandinavian coasts during 2009-2015, whereas the Canadian coast shows an albedo increase from 2009 to 2015. The maximum increase of the August albedo during 1982/1983 – 2014/2015 is 0.32 and the maximum decrease is -0.40. During 2008/2009 – 2014/2015 the corresponding increase for albedo in August is 0.31 and the decrease -0.27.

The variation of the Arctic surface albedo in June in 1982/1983 – 2014/2015 shows a decrease in a larger area, thus indicating that the sea ice concentration has decreased also in June. In Hudson Bay the location of sea ice changed from the western side to the eastern side. Also

of velocity and the CNES-CLS13 Mean Dynamic Topography. Ekman currents at two levels (surface and 15m) are calculated from an empirical model. The model parameters (amplitude and angle) have been derived as to minimize the misfit between wind stress data and the ageostrophic component extracted from in-situ drifter velocities (SVP drifters at 15m depth, Argo floats at the surface).

A regional product for the Mediterranean Sea has also been produced over the same time period. Obtained currents have been validated through comparison to independent in-situ observations and other existing products based either on observations or model outputs.

Arctic sea ice albedo time series 1982-2015 according to the CLARA-A2-SAL product by CM SAF

Author Terhikki Manninen

Affiliation Finnish Meteorological Institute

Co-authorsK. Anttila (Finnish Meteorological Institute), T. Manninen (Finnish Meteorological Institute), E. Jääskeläinen (Finnish Meteorological Institute), A. Riihelä (Finnish Meteorological Institute)

A new 34 –year long time series of surface albedo was used to study the changes in the albedo of the Arctic sea ice. The study is based on the surface albedo monthly

Section 2 – Observations for reanalyses

A 24 year observation-based reanalysis of ocean surface currents from the GlobCurrent project

Author Marie-Hélène Rio

Affiliation CLS

Co-authorsC. Dufau (CLS), H. Etienne (CLS), S. Mulet (CLS), G. Larnicol (CLS), J. Johannessen -NERSC), C. Donlon (ESA)

Accurate estimate of ocean surface currents is both a challenging issue and a growing end-users requirement. Advancing the quantitative estimation of ocean surface currents from satellite sensor synergy and demonstrating the impact in user-led scientific, operational and commercial applications was the main objective of the GlobCurrent project, a Data User Element (DUE) from the European Space Agency (ESA) which run from October 2013 to June 2017.

In the framework of this study, a global reanalysis of 24 years (1993-2016) of global ocean currents at two depths (surface and 15m) has been calculated as the sum of the geostrophic and Ekman components. The geostrophic component is based on the SSALTO-DUACS multi-mission altimeter maps


Predictions regarding the future climate and the state of African tropical forest remain uncertain in part due to a lack of legacy data which provides the necessary climatological and ecological context for current research in the Congo Basin. Even today, the central Congo Basin is currently represented by only a few rain gauges, limiting climate forecasts across the Congo Basin. This lack of long-term (historical) climatological data leaves the central Congo Basin spatially and temporally under-represented. However, old climate records could provide valuable information in support of climate re-analysis.

The historical archives of La régie des plantations de la colonie (REPCO) and the Institut National d’Etudes Agronomique du Congo Belge (INEAC), cover six decades (1901–1960). Located at the State Archives of Belgium, the Royal Museum for Central Africa and the Botanic Garden Meise, they hold vast amounts of (eco-) climatological data, with great potential and relevance for basic and applied research in the central Congo Basin.

Their scientific value resides in the extent of the data collected in a region where the availability of reliable baseline measurements are practically absent. The COBECORE project (http://cobecore.org) aims to establish baseline climatological measurements, crucial for reanalysis, by valorizing climatological legacy data through computer vision, machine learning and citizen science

In this framework, ARMOR3D have been compared with 6 other global ocean reanalysis/reprocessing products of CMEMS: an optimal interpolation of in-situ T/S profiles (CORA-OI from Coriolis), 4 reanalysis (GLORYS2V4 from Mercator Océan, ORAS5 from ECMWF, FOAM/GloSea from Met Office and C-GLORS from CMCC) and the ensemble mean of these reanalysis (GREP).

In this presentation, the main steps of the ARMOR3D and the combined SSS/SSD production systems are described. Then, results from ocean reanalysis/reprocessing intercomparison are presented: hydrographic variability are analyzed in all products in terms of spatial patterns and time evolution. Robust features and weaknesses are highlighted and uncertainty levels are provided.

COBECORE: recovering (eco-)climatological data from Belgian colonial archives.

Author Koen Hufkens

Affiliation Harvard University

Co-authorsKim Jacobsen (1), Hans Beeckman (1), Piet Stoffelen (2), Filip Vandelook (2), Jan Van den Bulcke (3), Michael Amara (4), Hans Verbeeck (5).

1: Xylarium, Royal Museum for Central Africa, 2: Botanic Garden Meise, 3: Laboratory of Wood Technology, Ghent University, 4: State Archives Belgium, 5: CAVElab, Ghent University

in-situ profiles for instance or which offer only a surface view of the ocean as satellite data.

The originality of the ARMOR3D observation based product is to take advantage of the strengths of these 2 types of data by combining satellite SLA and SST datasets with in-situ T, S vertical profiles in order to build a global 3D weekly temperature, salinity and geostrophic velocities fields at a spatial 1/4° resolution.

The mesoscale content of the satellite data and the vertical sampling of the in-situ profiles are complementary in this statistical approach. Also, this method need to use a reliable mesoscale SSS field. We use the combined SSS/SSD field computed at CNR from an optimal interpolation of in-situ data using SST gradients to add mesoscale features. ARMOR3D and the combined SSS/SSD products are part of the Copernicus Marine Environment Monitoring Service (CMEMS) through the Global observation component of the Global Monitoring and forecasting center.

A full reprocessing from 1993 to 2016 and near-real-time fields since 2014 are available through the CMEMS web portal. The range of applications of this product goes from mesoscale to large-scale studies. It could be used both for the evaluation of re-analyses and for ocean climate studies. For instance, ARMOR3D contributes to the annual CMEMS Ocean State Report (OSR).

technique, and describe how GPS-RO measurements are assimilated in ERA5. We will demonstrate that the GPS-RO measurementsreduce stratospheric biases in ERA5, and that GPS-RO and AMSU-A channel 14 provide complementary information.

More specifically, it will be demonstrated that AMSU-A channel 14 can constrain biases in the GPS-RO “null-space”. We will also present new results assessing the quality and impact of data from GPS/MET mission from 1995-1997. Although the GPS/MET data availability is sporadic, we will show that it is still a useful dataset for testing reanalysis systems during this period.

CMEMS multi-observations products to monitor ocean state

Author Sandrine Mulet

Affiliation CLS

Co-authorsStéphanie Guinehut (CLS), Nathalie Verbrugge (CLS), Bruno Buongiorno-Nardelli (CNR), Riccardo Droghei (CNR), Marie Drévillon (Mercator-Océan), Jérome Gourrion (CNRS/Coriolis), Andrea Storto (CMCC), Hao Zuo (ECMWF), Drew Peterson (UK Met Office)

To have a synoptic view of the 3D ocean to pursue oceanic studies, a multi observations gridded product can be often useful instead of using raw observations which can be irregularly distributed in space and time as the

Section 2


holds an archive of several collections of original historical world-wide weather records from land stations and ships.

The archive originates from the Deutsche Seewarte (German Marine Observatory), which was the predecessor organisation of DWD in Hamburg. The largest archive is the collection of meteorological logbooks from sailing ships and steamers. It contains about 37,000 individual journals with an estimated total amount of 23 Million observations that start in 1829 and end in 1945.

The majority of the observations are from the period from 1853 to 1934. The digitization procedure for the journals includes the registration of metadata, archiving of optical scans and manual transcription of the observations. The data are quality checked and transferred into a data base. About 11 Million observations are already stored in the data base. However, a large number of these observations have been digitized during previous decades and still have to be assigned a respective metadata record. Apart from ship observations, the Deutsche Seewarte also operated a world-wide net of overseas meteorological land stations, many of them situated at the coast or on islands.

The archive consists of more than 1500 stations, mostly from the periods from 1884 to 1943. Nearly 200 stations have already been digitized with a digitization procedure similar to that of the ship observations. Digitization of the data

The reference dataset has been validated simultaneously by both teams. An exhaustive comparison of the validation test results is now performed to find the best features of both datasets.

The study shows the differences between the EN4 and CORA validation results. It highlights the complementarity between the EN4 and CORA higher order tests. The design of the CORA and EN4 validation charts is discussed to understand how a different approach on the dataset scope can lead to differences in data validation. The new validation chart of the Copernicus Marine Service dataset is presented.

Data Rescue of Historic Observations from the Archives of the German Marine Observatory

Author Axel Andersson


Co-authorsB. Tinz (DWD), L. Gates (DWD)

Historic observational data records are an important contribution for climate reconstructions and analysis of past weather events. Particularly in remote and data sparse regions, such as the open ocean, newly rescued data can significantly improve the knowledge about weather and climatic conditions in earlier decades and centuries. Deutscher Wetterdienst (DWD, German Meteorological Service) in Hamburg

can also be found (Sea mammals profiles from MEOP, XBT datasets from cruises…). (EN4 also takes data from the ASBO dataset to supplement observations in the Arctic).

First advantage of this new merge product is to enhance the space and time coverage at global and european scales for the period covering 1950 till a year before the current year. This product is updated once a year and T&S gridded fields are alos generated for the period 1990-year n-1. The enhancement compared to the revious CORA product will be presented. Despite the fact that the profiles distributed by both datasets are mostly the same, the quality control procedures developed by the Met Office and Copernicus teams differ, sometimes leading to different quality control flags for the same profile.

Started in 2016 a new study started that aims to compare both validation procedures to move towards a Copernicus Marine Service dataset with the best features of CORA and EN4 validation. A reference data set composed of the full set of in-situ temperature and salinity measurements collected by Coriolis during 2015 is used. These measurements have been made thanks to wide range of instruments (XBTs, CTDs, Argo floats, Instrumented sea mammals,…), covering the global ocean.

approaches. Here we report on the first half year of data recovery of the first part of some 589 climatological stations spread throughout the Congo Basin (http://cobecore.org/map/). We discuss progress made in the automation of data recovery and issues regarding transcription and provide a short overview of preliminary data products.

Comparison of CORA and EN4 in-situ datasets validation methods, toward a better quality merged dataset.

Author Szekely Tanguy

Affiliation CNRS

Co-authorsR.Killick (Met Office), J.Gourrion (CNRS), A.Piron (Altran), G. Reverdin (LOCEAN)

CORA and EN4 are both global delayed time mode validated in-situ ocean temperature and salinity datasets distributed by the Met Office (http://www.metoffice.gov.uk/) and Copernicus (www.marine.copernicus.eu). A large part of the profiles distributed by CORA and EN4 in recent years are Argo profiles from the ARGO DAC, but profiles are also extracted from the World Ocean Database and TESAC profiles from GTSPP.

In the case of CORA, data coming from the EUROGOOS Regional operationnal oserving system (ROOS) operated by European institutes no managed by National Data Centres and other datasets of profiles povided by scientific sources

Section 2


Since about 15 years, the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF, www.cmsaf.eu) develops capabilities for a sustained generation and provision of Climate Data Records (CDRs) derived from operational meteorological satellites, which will be continued in the current phase until 2022. The ultimate aim is to make the resulting data records suitable for the analysis of climate variability and the detection of climate trends.

The product portfolio of the CM SAF comprises long time series of Essential Climate Variables (ECVs) related to the energy & water cycle as defined by Global Climate Observing System (GCOS). Thus, users have access to many parameters of the water and energy cycle based on operational satellite instruments, but also to fundamental climate data records based on microwave imager measurements thoroughly inter-calibrated and homogenized to be suitable for assimilation and integration into re-analyses efforts. The time series of the climate data records range from 8 to more than 30 years with a global coverage for data based on polar orbiting satellites, while those based on geostationary satellite data cover the region of the METEOSAT diskntil 2022 new editions of climate data records (CDR) will be published extending the time-range and the portfolio. In particular, new products related to the following topics will be developed and provided

EUMETSAF’s Climate Monitoring SAF: A sustained provision of Climate Data Records for Evaluation and Climate Monitoring

Author Rainer Hollmann


Co-authorsM. Schröder (Deutscher Wetterdienst), K. Fennig (Deutscher Wetterdienst), M. Stengel (Deutscher Wetterdienst), J. Trentmann (Deutscher Wetterdienst), P. Fuchs (Deutscher Wetterdienst)

In recent decades climate variability and change have caused impacts on natural and human systems on all continents. Observations are needed to understand and document these interactions of the climate system. They are increasingly based on remote sensing from satellites which offer global scale and continuous coverage. Only long term and consistent observations of the earth system allow us to quantify impacts of climate variability and change on the natural and human dimension. From this understanding one can estimate and eventually predict future states of the earth system and quantify its vulnerability and resilience to continuing anthropogenic forcing. In addition, these observations can be used in the evaluation and assessment of reanalyses data records and climate models.

For example, quality control, transmission interruptions, and station outages can occasionally affect data availability. While orbital paths can be known, drift in certain instruments and the large number of available instruments makes it challenging to know which satellite is observing any region at any point in the diurnal cycle.

Furthermore, there is information from the statistics generated by the data assimilation that can help understand the model and the quality of the reanalysis. Typically, the assimilated observations and their innovations are in observation-space data formats and have not been made easily available to reanalysis users.

A test data set has been developed to make the MERRA-2 assimilated observations available for rapid and general use, by simplifying the data format. The observations are binned to a grid similar as MERRA-2 and saved as net CDF. This data collection includes the mean and number of observations in the bin as well as its variance.

The data will also include the innovations from the data assimilation, the forecast departure and the analysis increment, as well as bias correction (for satellite radiances). We refer to this proof-of-concept data as the MERRA-2 Gridded Innovations and Observations (GIO). In this paper, we present the data format and its strengths and limitations with some initial testing and validation of the methodology.

from China, Korea, the tropical Pacific, Cameroon and Togo and Canada has been completed. The presentation will show the recent progress of the digitization efforts and ongoing analysis of the data.

An important activity is the further development of automatic quality control procedures, where the main task is to adapt the modern QC limits to the lower accuracy of the historical observations, different weather classifications, units and conventions.

Development of Gridded Innovations and Observations supplement to MERRA-2

Author Michael G. Bosilovich

Affiliation NASA GSFC GMAO

Co-authorA.M. da Silva (NASA GSFC GMAO)

Atmospheric reanalysis have become an important source of data for weather and climate research, owing to the continuity of the data, but especially because of the multitude of observational data included (radiosondes, commercial aircraft, retrieved data products and radiances). However, the presence of assimilated observations can vary based on numerous factors, and so it is difficult or impossible for a researcher to say with any degree of certainty how many and what type of observations contributed to the reanalysis data they are using at any give point in time or space.

Section 2


But, it is not very clear about SCV and its severe weather because of the absence of meteorological station and the sparse of observing data. The research and the understanding on SCV and its torrential rain are seriously restricted. Based on the situation of scientific research and operational forecast for SCV, this paper discusses the field experiment of SCV and its importance for short-term weather forecast. And the intensive observation scientific experiment of SCV has been carried out in summer from 2010 to 2017.

The intensive observation data for SCV activities and its weather processes has been obtained, and using the multi-source data from the surface, radiosonde, radar observation in daily weather forecast operation, it has been effectively improved the forecast for SCV and its torrential rain. The basic feature and anomalous evolution of SCV have been deeply and refinedly analyzed in weather map, which further reveal the structural feature, development process and weather influence of SCV.

Furthermore, the radiosonde data assimilation, from the intensive observation scientific experiment of SCV, obviously improves the operation ability of the numerical weather forecast in Southwest China. In a word, it is necessary to reinforce the field experiment and expand data application for the forecast of SCV and its torrential rain.

evaluated data available at 20CRv2 and its newer version (20CRv2c) for Calm Bay (Buchta Tikhaya) located in the Franz Josef Land archipelago for the period 1930–1940. This study investigated the quality of reanalyzed surface quantities, such as 2-m air temperature, 2-m specific humidity and 10-m horizontal wind speed. Comparison of vertical temperature structure produced by two versions of 20CR at Calm Bay was based on data taken from PANGAEA – Data Publisher for Earth & Environmental Science. This digital data library provides a historical archive of radiosondes and tracked balloons on standard pressure levels back to the 1920s.

Field experiment of Southwest China vortex and its applications in short-term weather forecast

Author Yueqing Li

Affiliation Institute of Plateau Meteorology, China Meteorological Administration, & Heavy Rain and Drought Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province

The Southwest China vortex (SCV) is a very important influence system for the precipitation weather of China during summer half year. And the torrential rain of SCV is also a much complex and distinctive torrential rain in China. SCV and its torrential rain are always a key scientific problem in weather research and forecast.

Our confidence in using these data sets to reconstruct past climate variability requires careful efforts to validate them against observations, especially in the Arctic, where the network of meteorological stations is sparse. In this paper we have compared different kinds of measured meteorological data with reanalysis products. Early-instrumental (1801–1920) atmospheric pressure data from land stations covering the entire high Arctic have been compared with data (grids located nearest the historical sites) taken from the 2nd version of the 20th Century Reanalysis Project (20CRv2).

Another of our evaluations used air temperature taken from 20CRv2 and ERA20C reanalyses for the warm half-year in the periods 1871–1910 and 1901–1910, respectively. Data covered the maritime part of the Svalbard archipelago (74–82°N, 6–30°E). The majority of the data were taken from a Norwegian collection entitled Arctic Norwegian Logbook Data: 1867–1912 available at the Computational Information Systems Laboratory Research Data Archive (CISL RDA). Besides data downloaded from the CISL RDA, we also used air temperature data digitized from logbooks gathered by us as part of various data recovery projects. In this research we have compared air temperature data from observations made on ships and available in logbooks.

Analysis was conducted for four regions (grid boxes, 4° latitude × 12° longitude) NW, NE, SW and SE. Finally, we

during CDOP 3 global precipitation (ocean and land), regional land fluxes (Meteosat domain), global high clouds. This presentation will highlight results from the currently available CDRs and will present an overview of the upcoming new editions of CDRs.

Evaluation of reanalyses for the Arctic based on instrumental historical observations

Author Rajmund Przybylak

Affiliation Nicolaus Copernicus University, Department of Meteorology and Climatology

Co-authorsP. Wyszynski (Nicolaus Copernicus University, Department of Meteorology and Climatology), D. Klaus (Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research), K. Dethloff (Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research), A. Rinke (Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research), T. Strzyzewski (Nicolaus Copernicus University, Department of Meteorology and Climatology)

The development of atmospheric reanalyses that assimilate only surface data thereby allowing one to extend the period of the datasets back to the mid 19th and early 20th century is one of the most significant advances in climate sciences.

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Gridded, high-resolution observational data sets for Southeast Asia and South America

Author Gerard van der Schrier

Affiliation Royal Netherlands Meteorological Institute (KNMI)

Co-authorsE.J.M. van den Besselaar (KNMI), R. Cornes (KNMI, CRU), A. Suwondo (BMKG), Iqbal (BMKG), A.M.G. Klein Tank (KNMI)

Validation for reanalyses datasets requires access to high-quality andhigh-resolution observational datasets. For Europe, the gridded dailytemperature and precipitation fields of the E-OBS dataset, based onthe meteorological station data provided by the European NationalMeteorological Services (NMSs) to ECA&D (www.ecad.eu), has been usedfrequently for these purposes. Using a similar approach, the SoutheastAsian Climate Assessment & Dataset (SACA&D) has been developed in a collaboration with NMSs from the region.

Based on the meteorological station data, a gridded dataset providing daily maps of temperature and precipitation has been developed. This data set, SA-OBS, is introduced in this presentation. The spatial resolution of these maps are 0.25 x 0.25 degree, and data spans the

bias adjustment scheme from radiosonde temperature to radiosonde humidity measurements.

We use for example ERA-Interim to detect such breakpoints and to adjust the time series to a globally more consistent data set. We apply two methods, one adjusts the mean between breakpoints whereas the other adjusts the quantiles and thus the distribution of humidity.

For long-term trend estimates (1979-2016) of mean humidity both methods work well. For low and high percentiles, however, the distribution matching methods works better. We compare our results with ERA-Interim and demonstrate existing humidity biases in ERA-Interim.

On a preliminary basis we compare radiosonde humidity measurements also with brightness temperatures from microwave sounders (SSM/T-2, SSMIS). Results indicate still large discrepancies between brightness temperatures calculated from radiosondes and ERA-Interim employing RTTOVv11 compared to measured brightness temperatures from microwave sounders.

We adopted a Bayesian approach, since the data at the observation locations are honored and the spatial covariance structure of the spatial process is reproduced in each realisation. This generates more realistic fields than some interpolation method. In a second step, realisations of occurrence/non-occurrence of precipitation exceeding the same thresholds are obtained given the simulated latent process. HIRAIN is extended to several thresholds of precipitation amount. A final precipitation product with hourly temporal and 4 km spatial resolution is generated from the fields occurrence/non-occurrence of the individual thresholds.

Global bias-adjusted radiosonde humidity

Author Michael Blaschek


Co-authorL. Haimberger (University of Vienna)

Radiosonde humidity measurements are valuable because of their long-term availability and secondly because of high vertical resolution of the measurements. Nevertheless, no measurement system is without uncertainties and for radiosondes the changes in the observation system lead to more or less clear breakpoints in the observed long-term time series. These artificial jumps and biases need to be removed and we adapt a well-known

Generation of high resolution precipitation conditional on rainfall observations and infrared brightness temperature

Author Ieda Pscheidt

Affiliation University of Bonn, Meteorological Institute

Co-authorsPetra Friederichs (University of Bonn, Meteorological Institute), Dan Cooley (Colorado State University, Department of Statistics), Jennifer Hoeting (Colorado State University, Department of Statistics)

This study is part of a high resolution reanalysis project proposed for Germany and Europe (Bollmeyer et. al., 2014). The reanalysis for Germany assimilates precipitation among other variables. For periods after 2007 radar data is used for this purpose. However, for earlier periods when radar data is not available another high resolution precipitation dataset is required.

To meet this need we propose the method HIRAIN to generate an ensemble of probable space-time precipitation fields given a dataset of rainfall observed by synoptic stations and infrared brightness temperature from Meteosat Second Generation. HIRAIN works in two steps.

First, a Bayesian statistical model conditional on the observational data simulates the latent spatial Gaussian process that drives the occurrence of precipitation exceeding a selected threshold.

Section 2


description of the new features included in R3.0 that further support and augment reanalysis studies.

The R3.0 data and metadata characteristics will be described in a companion presentation. By using new IT infrastructure and IMMA1 format enhancements, R3.0 now has new ocean-based data parameters, observing system bias adjustments developed and provided by experts whose contributions create improved climate records, and assimilation model feedback from reanalysis efforts.

Unique report-level identifiers link all of these components together to support traceability back to individual core records and further strengthen the data provenance. Details about the content in these components as well as their current status will be described to illustrate the new data that are available. Furthermore, the community is invited to contribute additional observing system adjustments and reanalyses feedback which then can be included as subsidiary records linked to the core R3.0 records.

The process and procedure to do so will be outlined. Uniquely, ICOADS as a foundational observation dataset is one of the first, if not the first, open access archive to capture significant components of the data life cycle. In this case, the ICOADS data life cycle includes routine new releases that add new data sources and coverage throughout the full

Decisions in the SOT have direct impacts on the Near-Real-Time product as well as other aspects of data collection and processing. Finally, we will also report on progress towards establishment of ICOADS as a Centre for Marine-Meteorological and Oceanographic Climate Data (CMOC), within the new WMO-IOC Marine Climate Data System (MCDS), which is anticipated to facilitate further longer-term improvements in the effective management and stewardship of marine and near-surface oceanographic data internationally.

ICOADS Release 3.0: New Relevance and Support for Reanalyses

Author Thomas Cram

Affiliation National Center for Atmospheric Research (NCAR)

Co-authorS. Worley (NCAR)

The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Release 3.0 (R3.0) brings into operational production new technical features and user-driven innovations that make it more data rich as both an input for and output from reanalysis products. This presentation will highlight the suite of product types and data access methods available from NCEI, NOAA ESRL/PSD, and NCAR, followed by a detailed

New or improved data sources cover various time periods, from the late 18th Century all the way into the modern period. These sources include newly digitized historical observations from collections such as the English East India Company and the German Maury collections, and updated external archives such as the Global Tropical Moored Buoy Array (GTMBA) and World Ocean Database (WOD).

A major observational format update is an extension to include near-surface oceanographic data elements such as salinity, nutrients and carbon cycle parameters. These parameters, with associated depths, have been populated from the WOD and other near-surface oceanographic sources. The new inclusion of a unique identifier (UID) to each individual marine report will help to improve traceability and facilitate collaboration between ICOADS users.

Future plans for ICOADS will be described in the second part of the presentation. The longstanding MARCDAT/CLIMAR user community will continue to actively help shape the database and improve data management to meet future needs and continue to make ICOADS a valuable resource for global climate research well into the future. The SOT is also a highly valuable and integral source of feedback and collaboration to ICOADS in keeping the dataset in tune with current observational procedures and instrumentation, as well as new sources of marine climate data.

period from 1981onwards. The gridding techniques used for this data set are similar as for the European data set.

The most recent developments are that for South America, in collaboration with NMSs in the region and the Climatic Research Unit (University of East Anglia, UK), a similar gridded dataset will be developed of which first results will be presented.

ICOADS Release 3.0: Data Characteristics and Future Priorities

Author Eric Freeman

Affiliation NOAA/NCEI/ERT, Inc.

Co-authorsA. Anderson (DWD), W. Angel (NOAA/NCEI), P. Brohan (Met Office), L. Gates (DWD), E.C. Kent (NOC), S. Smith (FSU), S. Worley (NCAR)

The latest update of the International Comprehensive Ocean-Atmosphere Data Set (ICOADS), Release 3.0 (R3.0), provides major coverage expansions on the previous version (R2.5) for 1662-2014, followed by improved monthly near-real-time (NRT) extensions, e.g. partly addressing the impacts of many masked Global Telecommunication System (GTS) ship callsigns since late 2007. This presentation will describe the data and metadata characteristics of R3.0, and provide details on new data sources and on extensive observational format updates.

Section 2


data exchange in the context of the WMO Marine Climatological Summaries Scheme (MCSS).

Several data streams are combined into a consolidated archive with a constantly increasing data amount. Real-time GTS data from ship, buoys and other marine measurement platforms are automatically stored in an interim database and are consolidated in near real-time for the archive. Secondly, Voluntary Observing Ship (VOS) data, which is collected by the Global Collecting Centres (GCC), is injected in delayed mode into the archive. In this context, DWD acts together with UK MetOffice as a contributing as well as a responsible member. In a third stream, newly digitized data from the historic ship journal archive of the DWD are continually added to the archive as well as other available sources. All incoming data sets are routinely checked with a sophisticated high quality control (HQC) procedure that performs several formal and meteorological checks on the data.

As part of the contributing member role in the GCC, German VOS data undergoes an additional manual quality control. In the light of the evolution of the WMO MCSS into the new Marine Climate Data System (MCDS) new forms of data management are implemented, such as flexible data access and product generation. Standardized data formats and metadata handling is essential to allow data exchange with external partners, e.g. ICOADS.

tool for the reanalysis production, itself. The web interface provides a quick tree-based overview on the complete observing system on one single page.

Instruments or satellites can be selected and time series of statistics on their usage can be plotted instantly from a previously created catalogue without the need of costly data retrievals. Besides this data discovery mode there is the possibility to download data. The OFA serves feedback data from the ERA-20C, ERA-Interim and ERA5 reanalysis. An overview will be presented as well as a real test case to demonstrate the importance of feedback data.

Observational Data from the Marine Data Climate Centre of Deutscher Wetterdienst

Author Axel Andersson


Co-authorsL. Gates (DWD), H. Otten-Balaccanu (DWD), M. Schulz (DWD)

The Marine Data Climate Centre of Deutscher Wetterdienst maintains an extensive climatological archive of quality controlled marine surface and atmospheric observations. Apart from recent data, the archive consists of a large amount of historic data ranging back to the mid-19th century. Data from the archive is used in a variety of application, such as operational climate monitoring and international

assimilate a wide range of satellite data (radiances, atmospheric motion vectors, scatterometer winds and ground-based GPS measurements).

The spread in the ensemble can be taken as a measure of the uncertainty in the reanalysis. It is to be hoped that improvements in the observation network over time lead to more reliable analyses with smaller uncertainty. Here this hypothesis is tested by comparing the ensemble spread for short periods run with and without satellite data.

Introduction to the Copernicus’s observation feedback archive

Author Gionata Biavati

Affiliation ECMWF

Co-authorH. Hersbach (ECMWF)

Within the Copernicus Climate Change Service (C3S), one task is the provision of easy access to observations that were ingested in global reanalysis as produced at ECMWF. Key feature is the inclusion of feedback information on how such observations were used, like how well they fitted the analysis products before and after assimilation,and estimates on biases and data quality.

This service will be provided by the web-based Observation Feedback Archive (OFA) as an integral part of the Climate Data Store (CDS) toolbox,with the aim is to reach a wide range of reanalysis users. In addition it forms a relevant monitoring

period of record (over 300 years), and is furthermore updated with modern data on a monthly basis.

This is supported by preservation in a long-term archive that freely distributes the data and related products and enables numerous flexible pathways to access the data. Finally, as will be described in this presentation, an operational system has been developed to receive information back from the data user community that captures the knowledge gained and makes it shareable with the next generation of users.

Impact of satellite data on reanalysis uncertainty for UERRA

Author Amy M. Doherty


Co-authorsR. Renshaw (Met Office, P. Jermey (Met Office), J. Davie (Met Office), S. Mahmood (Met Office)

UERRA (Uncertainties in Ensembles of Regional ReAnalyses) is an EU-funded project that provides high-resolution reanalyses over Europe, together with measures of uncertainty in those reanalyses. As a part of UERRA, the Met Office is running a single high-resolution reanalysis and a lower-resolution ensemble of reanalyses. These reanalyses cover the satellite era (1979-present). They

Section 2


quality control (QC) using NCEP GDAS QC procedures, a “PrepBUFR” to the so-called NCEP DUMP BUFR conversion tool were developed based on the python interface to NCEP BUFR library, and all the merged conventional observations were converted to DUMP format which is needed by GDAS QC procedure. The presentation will also introduce the collection and processing of AMV and GPS-RO. As a pilot experiment, the prepared observations will firstly being assimilated in a GFS/GSI-3DVar based interim reanalysis (CRA-Interim) covering 10-years from 2007 to 2016. We also intend to present some initial results of observation minus analysis and background from this pilot experiment.

On the Use of Sea Level Climate Data Record (CDR) for Reanalyses Evaluation

Author Jean-Francois Legeais

Affiliation CLS

Co-authorsY. Faugère (CLS), G. Taburet (CLS), MI. Pujol (CLS), G. Larnicol (CLS), B. Meyssignac (LEGOS)

Sea level is a very sensitive index of climate change and variability. Sea level integrates the ocean warming, mountain glaciers and ice sheet melting. Accurate monitoring of the sea level is required to better understand its variability and changes as well as the exchanges between ocean, land, cryosphere, and atmosphere. The satellite altimeter

Meteorological Information Center, CMA), Kaixi Hu (National Meteorological Information Center, CMA), Zhe Chen (National Meteorological Information Center, CMA), Hui Jiang (National Meteorological Information Center, CMA), Chenghu Sun (National Meteorological Information Center, CMA), Qi Zhao (National Meteorological Information Center, CMA)

CMA started global reanalysis efforts at the end of 2013 to produce CMA 40-year atmospheric reanalysis (CRA-40) extending back to 1979. As observations assimilated in the NCEP climate forecast system reanalysis (CFSR) covering from 1979 to 2014 and in the NCEP operational global data assimilation system (GDAS) archive from 2014 to present were collected, the basic idea for CRA-40 observations preparation is that, 1) use satellite radiances in CFSR/GDAS observation database directly; 2) add more Chinese observations to CFSR/GDAS database for conventional observations; 3) try to use the latest reprocessed AMV and GPS-RO observations from various organisations.

At this point, the presentation will focus on the processing of conventional observations, AMV and GPS-RO. Chinese radiosonde, SYNOP, Ship/Bouy observations and aircraft observations collected from various data sources were firstly converted to “PrepBUFR” format (same as CFSR observations) and then merged to CFSR/GDAS database. In order to perform online

compilation and quality control, and error assessment. Such efforts took place within the ERA-CLIM2 project, aiming at providing a better observational basis for reanalyses. The work on observations ideally is one cycle ahead of the generation cycle of reanalyses, allowing them to make full use of it.

In this paper we describe the activities within ERA-CLIM2, which range form upper-air data rescue to satellite data recalibration and from the generation of snow cover products to the development of a global station data metadatabase. The data generated feed into global repositories and serve future reanalysis projects.

Observations Processing for CMA 40-year atmospheric reanalysis (CRA-40)

Author Lipeng Jiang

Affiliation National Meteorological Information Center, CMA

Co-authorsZhiquan Liu (NCAR), Chunxiang Shi (National Meteorological Information Center, CMA), Zijiang Zhou (National Meteorological Information Center, CMA), Tao Zhang (National Meteorological Information Center, CMA), Jie Liao (National Meteorological Information Center, CMA), Zhisen Zhang (National Meteorological Information Center, CMA), Minyan Wang (National Meteorological Information Center, CMA), Shuang Yao (National Meteorological Information Center, CMA), Lijuan Cao (National

The presentation will give an overview of the marine data management at DWD that includes all stages from data collection by the port meteorological officer to data quality assurance and aggregating into marine data products. Current developments such as new routines for automatic and manual HQC, migration of the data archive to a high performance data base system to facilitate user access will be highlighted as well as present and planned data products for a variety of applications.

Observations for Reanalyses – Lessons from ERA-CLIM2

Author Stefan Brönnimann

Affiliation University of Bern

Co-authorsERA-CLIM2 WP3 team

Global dynamical reanalyes of the atmosphere and ocean fundamentally rely on observations, not just for the assimilation (i.e. for the definition of the state of the Earth-system components), but also in many other steps along the production chain. Observations are used to constrain the model boundary conditions, for the calibration of transfer function or retirevals, for error determination of observations, and for the evaluation of data products.

This requires major efforts on the side of observations, including data rescue (for historical observations), data management (including metadatabases),

Section 2


Quantifying The Improvement In Reanalysis Accuracy Due To Hobbyist Weather Stations

Author Khaled Sharif

Affiliation ArabiaWeather Inc

Co-authorM. Mansour (ArabiaWeather)

ArabiaWeather has, over time, created a large network of hobbyist weather stations distributed to volunteers around the Middle East and North Africa region, in an effort to cover areas that are too distant from traditional sources of observational data.

Due to the sparsity of existing weather stations, the region makes for a good case study regarding the improvement in reanalysis accuracy gained by increasing the number of weather stations at the surface level. In this paper, we attempt to quantify the accuracy improvement versus the amount of weather stations added, and also quantify the plateau effect that occurs once we reach a saturating point in terms of stations added.

We also attempt to geospatially visualize this increase in weather station density versus accuracy improvement, and quantify the relationships between distance, density, and accuracy. Finally, we propose a method to optimally choose locations for future weather stations in such a way that would maximize gained accuracy improvement.

In order to achieve this goal their inputs, observations, must be accurate, stable, and available over long time periods. Serving this need, the Fidelity and uncertainty in climate data records from Earth Observations (FIDUCEO) project reassesses satellite observations of different instruments, in terms of determine the uncertainty, recalibrating the measurements, and increasing the accuracy.

Within the presented study, we demonstrate an undertaking of preparing input satellite data for reanalysis in a research-to-operations mode. A Fundamental Climate Data Record (FCDR) of the High Resolution Infrared Radiation Sounder (HIRS) is prepared, based on the latest science including metrological principles. This means not only revising the calibration and investigating inter-satellite biases, but also determining all the associated uncertainties.

In this presentation, the focus is put on the very first instruments that have been rarely investigated until now. The time series of HIRS on board of NIMBUS-6, TIROS-N, NOAA-6, and NOAA-8 is analysed and their stability and variability is presented and compared to those of the new and more stable instruments, such as on METOP-A and METOP-B. Further, C3S builds on the experience and achievements of FIDUCEO. Thus, this presentation will show results of FIDUCEO on the increased accuracy of HIRS radiances due to revised calibration and in depth uncertainty analysis.

presented. Then, the characteristics and limits of the different products described above (C3S, CMEMS) will be presented in order to help the ocean and climate community on their optimal use for validation, assimilation activities as well as scientific studies.

Preparing HIRS radiances as input to Reanalysis within the Copernicus Climate Change Service

Author Timo Hanschmann


Co-authorsG. Holl (University of Reading, reading, UK), V. John (EUMETSAT, Darmstadt, Germany), R. Roebeling (EUMETSAT, Darmstadt, Germany), J. Schulz (EUMETSAT, Darmstadt, Germany)

Availability of operational satellite observations on a multi decadal time scale leads to an increased use of them in reanalysis and climate studies, e.g., for the investigation of climate trends and feedbacks. However, to detect and evaluate climate trends and feedbacks, the time series need to have a high temporal consistency, accuracy (small bias), and precision (high signal to noise ratio). One objective of the Copernicus Climate Change Service (C3S) is to provide improved global and regional reanalysis data that meet these requirements.

sea level has been measured by different successive missions since 1993. More than 70 cumulated years of measurements have now been reprocessed with the DUACS (Data Unification and Altimeter Combination System) production system.

In addition of the altimeter instrument, the sea level estimation strongly relies on other complex systems such as orbit solutions, reference fields and oceanic/atmospheric geophysical corrections. During the past 6 years (2011-2017), the ESA Sea Level Climate Change Initiative has been the opportunity to improve the homogeneity and stability of the altimeter sea level record.

Today, the altimeter sea level is used for two main kinds of applications: (i) The retrieval of mesoscale signals in the context of ocean modeling and analysis of the ocean circulation at global or regional scale. This requires the most accurate sea level estimation at each time step with the best spatial sampling of the ocean. Such dataset is produced within the Copernicus Marine Service (CMEMS) (previously distributed by AVISO). (ii) The monitoring of the long-term evolution of the sea level for climate applications and the analysis of Ocean/Climate Index (such as the global and regional Mean Sea Level evolution).

This requires a homogeneous and stable sea level record. Such dataset is produced within the Copernicus Climate Service (C3S). The main steps of the altimeter production system will be

Section 2


Recovering (eco-)climatological data from Belgian colonial archives

Author Innocent Banzi Ngulu-kulu

Affiliation Ghent University

Co-authorsKim Jacobsen (Xylarium, Royal Museum for Central Africa), Tom de Mil (Xylarium, Royal Museum for Central Africa), Jan Van den Bulcke (Laboratory of Wood Technology), Hans Verbeeck (CAVElab, Ghent University), Koen Hufkens (Richardson Lab, Harvard University)

The COBECORE project (http://cobecore.org) aims to establish baseline climatological measurements by valorizing climatological legacy data, crucial for reanalysis. This lack of long-term (historical) climatological data leaves the central Congo Basin spatially and temporally under-represented. Even today, the central Congo Basin is currently represented by only a few rain gauges, limiting climate both retrospective analysis and forecasts across the Congo Basin. Here we present the historical context in which measurements were made by La régie des plantations de la colonie (REPCO) and the Institut National d’Etudes Agronomique du Congo Belge (INEAC), covering six decades (1901 – 1960). We discuss the rationale behind the establishment of various measurement stations, the protocols used as well as instrumentation. Our analysis

The recalibrated radiances are used to derive products such as clear and all sky radiances as well as Atmospheric Motion Vectors that can be assimilated into models used for reanalysis. In addition, the data are also used to derive Global Climate Observing System Essential Climate variables such as sea and land surface temperature, cloud properties, upper trophospheric humidity etc.

Recent developments in the European Climate Assessment & Dataset

Author Gerard van der Schrier

Affiliation Royal Netherlands Meteorological Institute

Co-authorsE. van den Besselaar (KNMI), C. Photiadou (KNMI), A. Squintu (KNMI), R. Cornes (KNMI, CRU), A. Klein Tank (KNMI), G. Verver (KNMI)

The European Climate Assessment & Dataset aims to provide daily meteorological station-baseddata and analysis for scientific research in and outside the climate sciences. An important contribution to this activity is the E-OBS, with is the gridded data set with daily maps of temperature,precipitation and pressure for Europe, based on ECA&D. In this presentation the latest changes to the ECA&D station coverage and products are shown. Emphasis will be on the newly introduced Quality Control procedures and homogenization of daily temperature data

applied to the imagers’ infrared and water vapour channels (at ~11 μm and ~6 μm, respectively) on both EUMETSAT and JMA geostationary satellites, i.e., VISSR/JAMI/IMAGER on the GMS/MTSAT series and MVIRI/SEVIRI on the METEOSAT series. Data from the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS) and High Resolution Infrared Radiation Sounder (HIRS/2) were used as references for recalibration.

The referencing was performed at the HIRS/2 channel’s spectral response that shows the best fit to the instruments in geostationary orbit. To keep the time series of reference measurements the same, AIRS and IASI spectra were convoluted using the HIRS/2 spectral response, which revealed very small uncertainties as compared to directly using hyper-spectral sounder spectra convoluted with the spectral response from the geostationary instruments. Collocated geostationary counts and the reference radiances are then regressed to derive re-calibration coefficients for each geostationary instrument.

This research contributes to the WMO initiative Sustained and Coordinated Processing of Environmental Satellite data for Climate Monitoring (SCOPE-CM) project No. 6: Inter-calibration of imager observations from time-series of geostationary satellites (IOGEO), which aims at establishing spatially and temporally homogeneous radiance data from all geostationary satellites.

Re-calibration of Infrared and Water Vapor channels of imagers on EUMETSAT and JMA geostationary meteorological satellites

Author Viju John


Co-authorsT. Tabata (JMA), R. Roebeling (EUMETSAT), F. Ruethrich (EUMETSAT), T. Hewison (EUMETSAT), J. Schulz (EUMETSAT)

Geostationary meteorological satellites have been observing the Earth for more than 40 years to support weather nowcasting and forecasting and other environmental applications. Due to their long observation period, good temporal sampling and spatial coverage, these observations could be of tremendous value for climate studies, such as on cloud properties and their impact on the global radiation budget.

They are also shown valuable for assimilating into Numerical Weather Prediction models used for generating reanalysis products. Climate applications require high accuracy satellite observations or at least a quantification and correction of effects due to changes in the characteristics of satellites and sensors that appear during their operational lifetime.

This presentation addresses a common re-calibration approach that has been

Section 2


The effective use of scatterometer winds in current and future GMAO reanalysis

Author Mohar Chattopadhyay

Affiliation Sceince Systems and Applications Inc./GMAO, NASA Goddard Space Flight Center

Co-authorsW. McCarty (GMAO, NASA Goddard Space Flight Center, Greenbelt, MD, USA

Scatterometer-derived near-surface ocean vector wind retrievals provide global measurements complementary to the sparse conventional observing system which primarily consists of ships and buoys over water surfaces. The RapidScat instrument was flown on the International Space Station as a quick and low cost replacement of QuikScat and as a continuation of the NASA scatterometry data record.

A unique characteristic of RapidScat was that it flew in a non-sun synchronous orbit at an inclination of 51.6 degrees. This orbit allowed for the collocation of measurements with other scatterometers as well as an ability to sample diurnal signals. In the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis, the scatterometry record began with the ESA European Remote Sensing (ERS) scatterometer on 5 Aug 1991 and continued through today with the EUMETSAT Metop Advanced

records from the two sensors, located at different depths, were revisited with the help of reanalysis products as a proxy for the sea-state. The differences between the two sensors can be reduced from 0.21 K RMS to 0.06 K RMS after retaining only the situations that likely correspond to well-mixed SST. Accounting for individual buoy biases, the differences are further reduced to 0.02 K RMS.

This would tend to suggest a strong relationship of the relevance of SST measurement with depth and sea-state, and the importance of these factors when using in situ SST data for climate monitoring. Another result concerns potentially the temporal stability of buoy SST data. The HRSST buoys were first calibrated individually in certified laboratories.

Three buoys were recovered and the temperature sensors were brought back to a certified laboratory in 2016. Comparing the initial laboratory results with those of 2016, a temporal drift of about 0.01K/year is found for each of the three buoys. These results from so few buoys cannot be claimed to be significant. However, if confirmed, these results would have applications on the use of in situ SST buoy data as a reference, without any temporal drift correction, for the calibration and validation of satellite data and to monitor the climate.

Revisiting the data record of High Resolution Sea Surface Temperature drifting buoys: possible implications for climate monitoring

Author Paul Poli

Affiliation Météo-France

Between 2012 and 2015, the EIG EUMETNET Operational Service for surface marine observations (E-SURFMAR) and European partners funded and deployed drifting buoys equipped to measure High Resolution Sea Surface Temperature. The HRSST referred to three major improvements as compared to standard practices at the time. First, the positioning accuracy was increased, thanks to GPS instead of Argos. Second, the temperature was transmitted and reported at higher resolution, 0.01 K instead of 0.1 K. Third, each buoy used an individually calibrated temperature probe, instead of one picked from a batch calibration.

Note the first two improvements (but not the third) are now standard on most drifting buoys. In addition, some of these buoys were also fitted with two digital probes, one in the buoy hull around 17 cm depth, and another located around 45 cm depth (as part of a conductivity and temperature sensor).

This configuration, with two accurate sensors, offered near-optimal horizontal and temporal collocation. The data

provides contextual information critical to the proper valorization and interpretation of data collected within the COBECORE project.

Reducing uncertainty by data rescue

Author Philip Brohan


The Twentieth Century Reanalysis (20CR) has demonstrated the power of reanalysis as a tool for inferring long-term climate variability and change. In particular, it is an effective user of the limited historical observations record, adding value to the available observations. A key virtue of 20CR is that it is an ensemble product, and the distribution across the ensemble is an invaluable measure of uncertainty.

Using the relative entropy of the ensemble with respect to a climatolological distribution shows clearly the time and space variation of the reanalysis skill. The dominant factor inthe analysis skill is the availability of nearby observations for assimilation – making new observations available by systematic data rescue can generate large improvements in 20CR.

Section 2


after 2004. This study examines the potential for extending the use of limb-sounding observations at earlier times and into the future, so that future reanalyses may be more applicable to the study of long-term ozone changes. Historical data are available from NASA instruments: the Limb Infrared Monitor of the Stratosphere (LIMS: 1978-1979); the Upper Atmospheric Research Satellite (UARS: 1991-1995); Sounding of the Atmosphere using Broadband Emission Radiometry (SABER: 2000-onwards). For the post EOS-MLS period, the joint NASA-NOAA Ozone Monitoring and Profiling Suite – Limb Profiler (OMPS-LP) instrument was launched on the Suomi-NPP platform in 201x and is planned for future platforms. This study will examine two aspects of these data pertaining to future reanalyses. First, the feasibility of merging the EOS-MLS and OMPS-LP instruments to provide a long-term record that extends beyond the potential lifetime of EOS-MLS.

If feasible, this would allow for long-term monitoring of ozone recovery in a three-dimensional reanalysis context. Second, the skill of the GEOS DAS in ingesting historical data types will be investigated. Because these do not overlap with EOS-MLS, use will be made of system statistics and evaluation using independent datasets. Impacts of using a complete ozone chemistry module will also be considered.

The dataset will be publicly available in NetCDF format, with the exception of a small fraction of the data (due to the policy of data providers); nonetheless the information derived from this fraction (e.g., for the homogeneity tests) will be public.

Towards a Representation of Vertically Resolved Ozone Changes in Reanalyses

Author Steven Pawson

Affiliation NASA GSFC

Co-authorsK. Wargan (NASA GSFC), C. Keller (NASA GSFC), W. McCarty (NASA GSFC), L. Coy (NASA GSFC)

The Solar Backscatter Ultraviolet Radiometer (SBUV) instruments on NASA and NOAA spacecraft provide a long-term record of total-column ozone and deep-layer partial columns since about 1980. These data have been carefully processed to extract long-term trends and offer a valuable resource for ozone monitoring. Studies assimilating limb-sounding observations in the Goddard Earth Observing System (GEOS) data assimilation system (DAS) demonstrate that vertical ozone gradients in the upper troposphere and lower stratosphere (UTLS) are much better represented than with the deep-layer SBUV observations.

This is exemplified by the use of retrieved ozone from the EOS Microwave Limb Sounder (EOS-MLS) instrument in the MERRA-2 reanalysis, for the period

Surface in-situ observations are affected by several problems, in particular by inconsistencies in space and time in the measurement procedures, and by the lack of information concerning these procedures. Moreover, human errors often contaminate the quality of the data in different ways. The absence of an official global repository for meteorological observations means that often data undergo numerous modifications by different users and different versions of the same series can be found even within the same collection, with usually no information on the modifications applied.

Within EUSTACE public collections (mainly GHCN-D, ISTI, and ECA&D) of daily maximum and minimum temperature observations, together with some additional dataset with restricted data policy, were merged. Duplicates were removed by comparing the observations in each individual year of each series with the data of the stations located within a 200 km radius.

Moreover, an automatic quality control algorithm was applied to all series. We also carried out an homogeneity assessment, by using four different breakpoint detection algorithms (three relative tests and one absolute test), and provide breakpoint locations for each series. The final result is a quality-controlled dataset of ca. 750 million unique observations over the period 1850-2015 that will be assimilated into other EUSTACE products.

Scatterometer (ASCAT). RapidScat, however, was not used in the MERRA-2 system as development had been completed prior to the beginning of its data record. In this presentation, the RapidScat ocean vector winds will be compared to MERRA-2, both in terms of the analysis fields and in the context of its global observing system, to assess the viability of using the data in future reanalysis systems developed by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center.

The EUSTACE daily LSAT dataset: A collection of 36000+ unique in-situ daily temperature series with inhomogeneities identified

Author Yuri Brugnara


Co-authorsS. Brönnimann (Oeschger Centre for Climate Change Research, University of Bern)

EUSTACE is a EU Horizon 2020 project whose goal is to produce daily estimates of surface air temperature since 1850 across the globe for the first time, by combining surface and satellite data using novel statistical techniques. As part of this, tens of thousands of in-situ data series were collected from various providers.

Section 2


EOFs allows the DA to respect the global scale teleconnections in the climate system. Experiments subsampling modern day observations to emulate historical data distributions are used to compare the performance of the EOF DA to a more standard DA using a shorter length scale Gaussian error covariance model.

The EOF DA method is shown to work efficiently in a 1/4 degree global configuration and does a good job of filling in the large data gaps. The system also allows a hybrid of the EOF and standard covariance models. This has the potential to allow us to formulate a DA system which works well both in the historical and in the modern period. An initial assessment of the hybrid approach will be presented.

Challenges in ERA5 data assimilation state-of-the-art system in the early satellite period

Author Cornel Soci

Affiliation ECMWF

Co-authorsH. Hersbach (ECMWF), A. Horanyi (ECMWF), C. Peubey (ECMWF), D. Schepers (ECMWF), A. Simmons (ECMWF)

ECMWF is currently producing the ERA5 atmospheric reanalysis under the framework of the EU-funded Copernicus Climate Change Service (C3S). ERA5 will

in both reanalysis work and for operational forecasts. This is the first time it is applied on HF radar data.

Assimilation using large scale EOF error covariances

Author Daniel J. Lea


Co-authorM.J. Martin (Met Office)

In modern ocean data assimilation (DA) systems it is common to use relatively isotropic and small length scale error covariance structures. The Met Office FOAM system, for example, produces a global 1/4 degree analysis using the NEMOVAR variational DA system with Gaussian error covariances with two length scales: one shorter length scale, the first baroclinic Rossby radius, and one longer length scale of 400 km.

These error covariances perform well with the modern ocean data distribution. Such error covariance models are, however, inadequate for DA in historical ocean and coupled reanalyses. Due to the historically inhomogeneous distribution of ocean observations, using these small scale error covariances leads to large areas of the ocean not being corrected and any analysis produced is not likely to be a globally realistic and consistent one.

We present an enhancement to NEMOVAR to use Empirical Orthogonal Function (EOF) error covariances. Using

product is validated by the comparisons with independent observations and other reanalysis products such as SODA, ECCO, GODAS.

Assimilation of HF radar ocean current data into NEMO-Nordic using 4D EnVar

Author Lars Axell

Affiliation SMHI

Baroclinic eddies in the ocean are at least one order of magnitude smaller than their atmospheric counterpart, being of the order of ten km rather than hundreds of km. One consequence of this is that ocean current magnitudes and directions are often difficult to forecast, unless an observation network of extremely high density is used. In practice, for currents this can be accomplished using coastally based High-Frequency radars measuring the radial components of the sea surface currents.

This poster presents results from assimilation experiments using an ensemble-based variational data assimilation method, 4D EnVar. It is shown that assimilation of HF radar data greatly improves the surface currents in the model NEMO-Nordic in the Skagerrak, off the west coast of Sweden. In it’s 3-D form, this assimilation method has earlier been used at SMHI for assimilation of SST, salinity and temperature profiles as well as sea ice,

Section 3 – Methods for reanalyses

An ocean reanalysis system

Author Changxiang Yan

Affiliation Institute of Atmospheric Physics, Chinese Academy of Sciences

Co-authorsJ. Zhu (Institute of Atmospheric Physics, Chinese Academy of Sciences), J. Xie (Institute of Atmospheric Physics, Chinese Academy of Sciences)

An ocean reanalysis system is developed based on the hybrid coordinate ocean model (HYCOM). The ensemble optimal interpolation which estimates the background error covariance matrix by the season-dependent ensemble composed of the long-term model ouputs is used. For in-situ ocean observations, the layer thickness, instead of temperature and salinity profiles, is assimilated.

For the HYCOM, the model bias lead to the inconsistency between the assimilation of in-situ observations and the assimilation of altimetry observations. Therefore, a new mean dynamical topography required by the altimetry data assimilation is obtained by the assimilation of Argo into the HYCOM.

The reanalysis experiment is carried out in the Indian and Pacific oceans during 1993-2015. The resultant reanalysis


The Oceanography Division of the Naval Research Laboratory has performed two ocean reanalyses, a 17-year (1999-2015) coupled ocean-sea ice reanalysis forced by NCEP CFS reanalysis fluxes and, in conjunction with the Marine Meteorology Division, a 7-year (2009-2016) coupled atmosphere-ocean-sea ice reanalysis.

The reanalyses are built upon the current Global Ocean Forecast System using the HYbrid Coordinate Ocean Model (HYCOM) and the Los Alamos Community Ice CodE (CICE). The ocean model has 41 layers and an equatorial resolution of 0.08° (8.8 km) on a tri-polar grid with the sea ice model on the same grid that reduces to ~3.5 km at the North Pole.

Sea surface temperature (SST), sea surface height (SSH) and temperature-salinity profile data are assimilated into the ocean using the Navy Coupled Ocean Data Assimilation 3D Var system (NCODA) every day. The SSH anomalies are converted into synthetic profiles of temperature and salinity prior to assimilation.

Incremental analysis updating of geostrophically balanced increments is performed over a 6-hour insertion window. For the coupled atmosphere-ocean-sea ice reanalysis, the same ocean-sea ice model configuration is used. However, the prescribed CFS fluxes are replaced by coupling to the NAVy Global Environmental Model (NAVGEM) with 50 levels and T359 (37 km) horizontal resolution.

system (2000-2014), based on a variational data assimilation scheme. As a proof-of-concept in constraining the global ocean heat budget for use in a coarse resolution ocean reanalyses and Earth system simulations, the methodology proves able to shape the global ocean heat content tendencies according to the TOA estimates, without compromising the accuracy of the reanalysis itself.

Spurious variability and under- (over-) estimation present in experiments with in-situ (no) data assimilation disappear when EEI data are assimilated. Similarly, the surface warming hiatus present without EEI data is significantly mitigated, inducing ocean warming at depths below 1500 m and slightly larger in the Southern Hemisphere, in qualitative accordance with many other recent studies.

Coupled high-resolution ocean-ice and ocean-atmosphere-ice reanalyses at the Naval Research Laboratory

Author James G. Richman

Affiliation Florida State University

Co-authorsE. J Metzger (Naval Research Laboratory, Stennis Space Center, MS USA) P. J. Hogan (Naval Research Laboratory, Stennis Space Center, MS USA) O. M. Smedstat (QinetiQ-North America, Stennis Space Center, MS USA)

This presentation describes the practical solution of recomputing the climatological part of the background term suited for this period. Horizontal correlation length scale become longer and vertical correlations broader. We also present results showing that in the 1980s, the quality control of the buoy network in the southern hemisphere has an important impact on improving the reanalysis quality.

Constraining the global ocean heat content through the use of CERES derived TOA Energy Imbalance estimates


Affiliation CMCC

Co-authorsC. Yang (CNR-ISAC), S. Masina (CMCC and INGV)

Clouds and the Earth’s Radiant Energy System (CERES) sensors onboard TERRA and AQUA Earth Observation satellites in combination with other space-borne sensors measure the reflected shortwave radiation and outgoing longwave radiation at the top of the atmosphere (TOA). The TOA net radiation budget (also referred to as the Earth’s energy imbalance, EEI) is stored in the oceans for the largest part.

In this study, we propose a procedure to assimilate global TOA radiation imbalance estimates from CERES in a coarse-resolution ocean reanalysis

span the period from 1950 to near-real time and will replace ERA-Interim. ERA5 employs a hybrid data assimilation system, namely a 10-member ensemble4D-Var data assimilation (EDA), at 62km horizontal resolution which generates a flow-dependent background error covariance matrix (hereafter the background term) to be used in a deterministic 4D-Var data assimilation system at higher horizontal resolution (31km).

The background term is a combination of a climatological part and a flow-dependent one. The climatological part of the background term depends on the observation density, geographical area and model resolution. The ERA5 data assimilation system utilises the ECMWF Integrated Forecasting System that was the operational model version in 2016 (though at lower resolution).

This version has been optimized to best use data provided by the current observing system. In particular, the climatological part of the background term has been generated based on the recent data rich period. For the early satellite period (1979/1980s) over the southern hemisphere, however, it appears challenging to obtain optimal reanalysis results. Although the EDA provides flow-dependent information, the required changes in the background term due to the sparser observing system are too large to be represented by errors of the day alone.

Section 3


CDA1 is applied to a coupled reanalysis experiment for the period from November 2013 to December 2015.

Comparison of the reanalysis result with Japanese 55-year Reanalysis (JRA-55) indicates that the overestimation of the sea surface latent heat flux found in JRA-55 disappears in the reanalysis of MRI-CDA1. The system also effectively suppresses the excess rainfall in the tropics in JRA-55, particularly in the Intertropical Convergence Zone (ITCZ) in the Pacific.

These improvements of MRI-CDA1 over JRA-55 mostly stems from improvements of atmospheric physical schemes in the coupled model. We are also conducting the uncoupled reanalysis using the MRI-CDA1. In the reanalysis, observational SST data are given instead of passing oceanic data from the ocean to the atmosphere in the coupled model.

Although the difference of the coupled reanalysis from the uncoupled one becomes much smaller than the difference from JRA-55, averaged error and root mean square error against an observation-based precipitation dataset (CMAP) are still reduced in a large part of the tropics and subtropics. We also found that the consideration of the ocean surface currents in the estimation of the momentum fluxes across the sea surface in the coupled system affects oceanic circulation and near-surface wind fields.

Evaluation of a Coupled Atmosphere-Ocean Data Assimilation System Reanalysis in JMA/MRI

Author Chiaki Kobayashi

Affiliation Meteorological Research Institute

Co-authorsY. Fujii (Meteorological Research Institute), C. Kobayashi (Meteorological Research Institute), T. Ishibashi (Meteorological Research Institute), Y. Takaya (Meteorological Research Institute), Y. Takeuchi (Meteorological Research Institute)

JMA/MRI has developed a weakly-coupled Data Assimilation (DA) system, MRI-CDA1, based on JMA’s operational systems. MRI-CDA1 is composed of the global atmosphere 4-Dimensional Variational (4D-Var) system for numerical weather predictions, NAPEX, the global ocean 3-Dimensional Variational (3D-Var) system for seasonal predictions, MOVE-G2, and the coupled atmosphere-ocean model for seasonal predictions, JMA/MRI-CGCM2.

The coupled atmosphere-ocean model is adopted as the outer model of the atmospheric 4D-Var routine, although the uncoupled atmospheric model is used as the inner model. The analysis increments of ocean temperature and salinity estimated by oceanic 3D-Var routine are adopted to the outer (coupled) model while integrating for prediction. MRI-

Effect of assimilating sparse weather observations in two different ensemble reanalyses



The Twentieth Century Reanalysis (20CR) and the CERA-20C coupled climate reanalysis are both ensemble products assimilating only surface observations. They assimilate almost the same set of atmospheric observations, but CERA uses more information from each observation, assimilating marine winds in addition to the surface pressures used by 20CR.

Comparison of the two ensembles, in a time and place where observations coverage is sparse, demonstrates the relationship between individual observations and analysis precision, and shows the effect of the different assimilation choices.

The coupling is done hourly using COARE 4.0 bulk fluxes on the ocean exchange grid. Following the lead of the Ocean Reanalysis Intercomparison Project (ORA-IP), the monthly mean upper ocean heat and salt content from the surface to 300 m, 700m and 1500 m, the mixed layer depth, the depth of the 20°C isotherm, the steric sea surface height and the Atlantic Meridional Overturning Circulation for the two NRL reanalyses and the Simple Ocean Data Assimilation (SODA 3.3.1) eddy-permitting reanalysis have been compared on a global uniform 0.5° grid.

The differences between the NRL coupled and uncoupled ocean reanalyses for the 7-year overlap period are small. The differences in heat and salt content increase with increasing integration depth and salt content differences are largest in the Southern Ocean. The differences increase when either NRL reanalysis is compared to SODA.

In addition, large differences in the equatorial circulation are found comparing SODA to either NRL reanalysis. In the Indian Ocean, the Equatorial Counter Current extends to far to the east and the subsurface flow in the thermocline is too weak in both NRL reanalyses.

Section 3


The assimilated data are limited to the observations with the systems operated for more than about 60 years such as the surface observations at the observatories and the upper air observations with radiosondes, maintaining the long-term consistency of the analysis quality. This experiment covers August 2014. The regional reanalysis is compared with two types of dynamical downscalings: one with time-integration uninterrupted over long-term and the other with time-integrations over short-term and reinitializations without assimilation.

The former type of dynamical downscaling often fails to reproduce synoptic-scale fields due to the internal variability. Assimilating only the conventional observations in addition to the forcing from the lateral boundaries successfully prevents the degradation, which is more apparent in the lower fields. The latter type of dynamical downscaling underestimates the precipitation due to insufficient spin-up accompanied by the reinitializations, although it captures the synoptic patterns appropriately.

The regional reanalysis, where the simulated fields in the previous cycles are inherited as first-guess, reduces the underestimation of precipitation. The configurations of this system are also discussed from the perspective on long-term regional reanalysis.

Is the regional reanalysis an alternative to the dynamical downscaling to reproduce the past meso-scale atmospheric fields?

Author Shin Fukui

Affiliation Tohoku University

Co-authorsToshiki Iwasaki (Tohoku University), Kazuo Saito (Meteorological Research Institute, Japan Agency for Marine-Earth Science and Technology), Hiromu Seko (Japan Agency for Marine-Earth Science and Technology, Meteorological Research Institute), Masaru Kunii (Japan Meteorological Agency)

We investigate the potential of the regional reanalysis assimilating only the conventional observations as an alternative to the dynamical downscaling to reproduce the past 3-dimensional high-resolution atmospheric fields for the studies of the local responses to the climate change and various meso-scale extreme events.

A preliminary experiment of regional reanalysis is conducted with the NHM-LETKF, which consists of the Japan Meteorological Agency’s non hydrostatic model and the local ensemble transform Kalman filter, applying the one-way double nesting to JRA-55. The inner and outer domains cover Japan and its surrounding area with a gird spacing of 5 km and the eastern part of the Asia with a gird spacing of 25 km, respectively.

0.25°x0.25° latitude/longitude grid using in-situ observations as well as satellite observations.

Use of the latter high-resolution SST/SIC is expected to improve quality of the reanalysis by better representing influences of oceanic eddies on atmosphere aloft and by improving the accuracy of radiative transfer calculations in satellite radiance data assimilation, although MGDSST is not available before 1981 due to the lack of input satellite data. In this study, we will present results of preliminary evaluation of SST/SIC from COBE-SST2 and MGDSST, focusing on comparison with other widely used SST/SIC products.

The topics to be presented include long-term trends and variabilities of global/regional SST and polar SIC, as well as spatial distribution of their climatology. In addition, we will also show results of preliminary experiments using the current version of JMA’s data assimilation system as a prototype for the JRA-3Q system to investigate the impacts of different SST/SIC BCs on analyzed atmospheric conditions. Based on these results, we will discuss an appropriate period to combine two SST/SIC BCs for JRA-3Q production.

Evaluation of SST/SIC Boundary Conditions for the Next Japanese Reanalysis: JRA-3Q

Author Masashi Harada

Affiliation Japan Meteorological Agency

Sea surface temperature (SST) and sea ice concentration (SIC) are important input data in a reanalysis since they are used as lower boundary conditions (BCs) for the atmospheric model and data assimilation system. In the past two Japanese reanalysis projects, i.e., JRA-25 (Onogi et al. 2007) and JRA-55 (Kobayashi et al. 2015), the used SST and SIC BCs were derived from COBE-SST (Ishii et al. 2005), which is a global century-long objective analysis dataset produced from only in-situ observations.

In the next Japanese reanalysis JRA-3Q (Japanese Reanalysis for Three Quarters of a Century), we are currently planning to utilize two SST/SIC products by the Japan Meteorological Agency (JMA): COBE-SST2 (Hirahara et al. 2014) for the period up to the 1980s and MGDSST (Kurihara et al. 2006) for the period thereafter. COBE-SST2, which is an improved version of COBE-SST, is produced on a 1°x1° latitude/longitude grid using basically in-situ observations only, whereas MGDSST is produced on a

Section 3


(SMOS) approach combined with meta-Gaussian spatio-temporal (MGST) random fields were used to this aim.

The SMOS approach used CFSR precipitation as covariate and is based on two regression models, the logistic regression to deal with rainfall occurrence and the vector generalized linear model in a Gamma distribution framework for the intensity. Two skill scores (Brier and continuous ranked probability skill scores) showed that estimated SMOS distributions had a better predictive power than the climatology for both precipitation occurrence and intensity.

Post-treated daily rainfall fields were then generated from SMOS daily distributions with the use of the MGST random fields to ensure persistence and spatial consistency in the series. Selected climate indicators (e.g., annual cumulative wet day or spatial correlation) were estimated for post-treated, observed and CFSR precipitation series. Comparisons between these indicators helped identify the advantages of using post-treated CFSR instead of CFSR, and highlighted which aspects of the daily post-treated sequences still need further investigations.

Post-treatment of the Climate Forecast System Reanalysis (CFSR) daily precipitations across the Great Lakes region (Canada)

Author Dikra Khedhaouiria

Affiliation INRS-ETE

Co-authorsA.M. Mailhot (Institut national de la recherche scientifique, Centre Eau Terre Environnement), A.C.F. Favre (Univ. Grenobles Alpes, CNRS, IRD, IGE, Grenoble INP)

The most important challenge that many countries faces, including Canada, is to characterize historical precipitation considering the low station density in many of their regions. Reanalysis, generated by Numerical Weather Prediction methods assimilating past observations, are an attractive alternative as they provide coherent, spatially and temporally continuous meteorological fields for a specific period and domain. However, reanalysis precipitations cannot be directly used as local estimates without post-treatments to correct bias and other errors.

The main objective of this study was to post-treat the CFSR gridded daily precipitation over the Great Lakes region in Canada to provide spatially-coherent local estimates of precipitation series at sites without historical records. The Stochastic Model Output Statistical

The use of these meteorological reanalysis datasets may solve uncertainty of data. In addition, phenomena such as rainfall evolution require the analysis of time series of ECMWF meteorological reanalysis datasets and the development of automated and reusable processing chains for monitoring rainfall evolution. We propose to formalize these processing chains from modeling an abstract and concrete models based on existing standards in terms of interoperability (International Standard Organisation ISO and OGC Open Geospatial Consortium). The use of these standards solves uncertainty of process. These processing chains modeled will be capitalized, and diffusible in operational environments. Our modeling approach uses work-context concepts. These concepts need organisation of human resources, data, and process in order to establish a knowledge-based connecting the two latter. This knowledge-based will be used to solve uncertainty of meteorological reanalysis datasets resources for monitoring rainfall evolution.

Modeling process chain of ECMWF reanalysis data to monitor rainfall evolution

Author Aimé Richard Hajalalaina

Affiliation Ecole de Management et d’Innovation Technologique, University of Fianarantsoa

Co-authorsAngelo Raherinirina (Ecole Normale Supérieure, Université de Fianarantsoa, Madagascar), Adolphe Ratiarison (Laboratoire de la Dynamique de l’Atmosphère, du Climat et de l’Océan, Université d’Antananarivo, Madagascar), Thérèse Libourel (Université de Montpellier, Montpellier, France)

In this paper, we propose a models of process chain and knowledge-based of meteorological reanalysis datasets that help scientists, working in the field of climate and in particular of the rainfall evolution, to solve uncertainty of spatial resources (data, process) to monitor the rainfall evolution in an area. Indeed, rainfall evolution mobilizes all research, various methods of meteorological reanalysis datasets processing are proposed. The ECMWF (European Centre for Medium-Range Weather Forecasts) meteorological reanalysis datasets available at present are voluminous and heterogeneous in terms of spatial and temporal resolutions (ERA-15, ERA-40, ERA-Interim and ERA-20C reanalysis).

Section 3


to reduce the analysis error and water budget residuals. The assimilation results indicate that the analysis error is reduced and the water imbalance is mitigated with this approach.

The application of variational data assimilation method on 2D tides model for Malacca Strait

Author Evie Hadrijantie Sudjono

Affiliation Marine Geological Institute

Co-authorsAgus Setiawan (Marine Research Center, Ministry of Marine Affairs and Fisheries, Indonesia)

A variational data assimilation method was applied in this study in order to improve the result of 2D tides model of Malacca Strait. Several available tidal measurement data were assimilated into the tides model by applying the conjugate gradient least square method.

By comparing the results of data assimilation model with forward model as well as independent data (measurement data that were not used in the assimilation), some improvements were obtained. This method can significantly reduce the over- and under-estimate results obtained by forward model.

pressure, surface humidity, surface wind, surface shortwave radiation, and surface precipitation.

Our assessment shows that indexes of CLDAS-V2.0 products are better than any other similar product in China. It is encouraging that CLDAS-V2.0 products has been used operationally in monitoring and forecasting of regional drought in Inner Mongolia, drought monitoring in Qinghai, and numerical prediction research in Beijing. A new land data assimilation system is under construction with the ability to assimilate soil moisture observations and satellite brightness temperature. We are looking forward to build the best land data assimilation system in China

Soil Moisture Assimilation Based on a Modified ETKF

Author Guocan Wu

Affiliation Beijing Normal University

Assimilating observations to a land surface model can further improve soil moisture estimation accuracy. However, assimilation results largely rely on forecast error and generally cannot maintain a water budget balance. In this study, shallow soil moisture observations are assimilated into Common Land Model (CoLM) to estimate the soil moisture in different layers.

A proposed forecast error inflation and water balance constraint are adopted in the Ensemble Transform Kalman Filter

air temperature, surface pressure, surface humidity and surface wind forcing data; As for shortwave radiation forcing data, we develop a new method based on DISORT method, rewrite code with parallel technology, use numerical forecast product and reanalysis data to replace climatic background field; we also use three land surface models (CLM3.5, CoLM and Noah-MP1-4) to gain a more steady and accurate land surface simulation using assemble method.(2) In high performance computing environment of China Meteorological Administration, we successfully develop CLDAS-V2.0 operation system with the standard of China Integrated Meteorological Information Sharing System (CIMISS). Using EC-Flow software, we build Land Surface Forcing Data Fusion Sub-system, Land Surface Assemble Simulation Sub-system, Product Service and Distribution Sub-system, Product Evaluation Sub-system, and Product Monitor Sub-system.

In the end, we build the first operational land data assimilation system in China, which has complete data acquisition, product production, product evaluation, product monitoring, product archiving, product distribution ability.(3) Based on comprehensive consideration of feedback from different research and operation users, we widen spatial coverage of our product and develop more land surface products including soil moisture, soil temperature, surface skin temperature, relative moisture of the soil, surface air temperature, surface

Progress of CMA Land Data Assimilation System (CLDAS)

Author Chunxiang Shi

Affiliation National Meteorological Information Center

Co-authorsZhiwei Jiang (National Meteorological Information Center), Xiao Liang (National Meteorological Information Center), Tao Zhang (National Meteorological Information Center), Lipeng Jiang (National Meteorological Information Center), Bin Xu (National Meteorological Information Center), Shuai Han (National Meteorological Information Center), Zhi Zhu (National Meteorological Information Center)

CMA Land Data Assimilation System (CLDAS) is founded by Multi-source Data Fusion Team in National Meteorological Information Center, China Meteorological Administration. In May 2017, second version of CLDAS (CLDAS-V2.0) has been put into operation In CLDAS-V2.0, we have three important progresses: (1)Through import and digestion, we realize key technologies of land surface multi-source data fusion and analysis, and transform these technologies from research to operation.

Based on previous survey, we choose STMAS developed by Xie as our method to fuse numerical forecast product and observations from more than 50000 surface meteorological observation stations to produce surface

Section 3


atmospheric component with a local ensemble transform Kalman filter (LETKF).

To assess the added value of using such a soil-vegetation-atmosphere-transfer-model in ensemble mode, we evaluate precipitation and soil moisture with respect to independent measurements and compare them to existing high-resolution atmospheric regional reanalyses as well as a pure dynamical downscaling experiment with the coupled TerrSysMP.

Using lagged covariances to assimilate RAPID data

Author Christopher Thomas

Affiliation Department of Meteorology, University of Reading

Co-authorsKeith Haines (Department of Meteorology, University of Reading), Irene Polo (Department of Meteorology, University of Reading), Jon Robson (Department of Meteorology, University of Reading)

The motivation of this work is to assimilate the observations of the AMOC made by the RAPID array at 26°N in the Atlantic Ocean by modifying ocean densities ‘upstream’ in the Labrador Sea. Previous studies have shown that the AMOC is robustly sensitive to anomalies in the Labrador Sea which occur at a time lag of several years earlier.

The representation of the diurnal to seasonal variability of the water cycle on small scales, needed for the representation of surface and sub-surface water flow in river catchments, is not well represented by current reanalyses. However, the interest in such data sets is increasing for hydrological and agricultural applications.

Recent studies on land surface simulations for specific river basins, with a finer grid spacing and driven by global reanalyses, show a significant improvement in the representation of soil moisture and precipitation. The next step would be to allow a feedback between the land surface and the atmosphere to take place, in order to achieve a sustainable effect on the water cycle within the terrestrial system as a whole. This study focuses on an ensemble of retrospective analyses of a short summer period for a catchment in the western part of Germany.

We utilize a limited area model setup at horizontal resolutions of 1 km for the atmosphere and 500 m for the land surface and soil. The simulations are based on the Terrestrial Systems Modeling Platform (TerrSysMP) which has the capability to exchange the relevant state vectors between the soil, vegetation and the atmosphere in either direction, thus representing a fully coupled terrestrial model approach.

In order to bring the model closer to observed precipitation, rain radar reflectivity is assimilated into the

By excluding the data during daytime, over sandy land, Tibetan Plateau, or with steep terrains, the brightness temperature simulations generated by the Community Radiative Transfer Model (CRTM) with the ECMWF LST and CAMEL_HSRemis database compare very well with the Advanced Himawari Imager (AHI) observations statistically and instantaneously. This study suggests that the AHI surface-sensitive channels over land could be effectively assimilated and contribute to improved numerical weather predictions.

Ultra-high resolution reanalysis for a river catchment

Author Clarissa Figura

Affiliation University of Bonn

Co-authorsA. Hense (Meteorologisches Institut der Rheinischen-Friedrich-Wilhelms Universität Bonn), J. Keller (Hans-Ertel-Center for Weather Research, Deutscher Wetterdienst), C. Simmer (Meteorologisches Institut der Rheinischen-Friedrich-Wilhelms Universität Bonn), I. Thiele-Eich (Meteorologisches Institut der Rheinischen-Friedrich-Wilhelms Universität Bonn), S. Wahl (Hans-Ertel Center for Weather Research, Meteorologisches Institut der Rheinischen-Friedrich-Wilhelms Universität Bonn)

Toward Assimilation of AHI Surface-sensitive Channels over Land – A Quantitative Assessment of Simulation Accuracy

Author Xiaoyong Zhuge

Affiliation Nanjing University

Simulations of surface-sensitive channels from geostationary imagers over land require accurate land skin temperature (LST) and infrared land surface emissivity (LSE). Compared with ground-based observations, large biases are found in the European Center for Medium range Weather Forecasting (ECMWF) LST analyses during daytime, over sandy land and Tibetan Plateau, and areas with terrain height differences between 0.25° and 1-min topography resolutions outside the range from -100 to 200m.

The Combined Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS) Emissivity over Land (CAMEL) High Spectral Resolution Emissivity database (CAMEL_HSRemis) have the highest accuracy than the International Geosphere-Biosphere Programme (IGBP) emissivity and the University of Wisconsin at Madison (UW) High Spectral Resolution Emissivity (UW_HSRemis) databases.

Section 3


between biased and nearby reference observations (which are assumed to be unbiased).

First, the bias correction system was tested using the Lorenz 63 model. Under most parameter regimes the VarBC scheme with observations-of-bias worked well. However, when the true bias was very small VarBC methods were found to slightly degrade the analysis relative to doing no bias correction. Under all circumstances the VarBC scheme including observations-of-bias outperformed a VarBC scheme without these observations.

Second, we show results from applying the VarBC scheme in a realistic setting using the NEMO ocean model and NEMOVAR data assimilation framework. The system is tested both for a period where reference data are plentiful, and for a period with only sparse reference data. Real data from the AQUA-AMSRE, NOAA-AVHRR and NOAA-METOP instruments are bias corrected. Reference data were taken from drifting buoys and the ENVISAT-AATSR instrument.

The system is compared to the output of the Met Office’s current offline bias correction scheme. In these experiments the bias correction was found to reduce SST biases in the model background relative to the reference data.

Variational bias correction of Sea Surface Temperature observations

Author Daniel J. Lea


Co-authorsJ. While (Met Office), M.J. Martin (Met Office)

Observations can contain significant systematic error. With Sea Surface Temperature (SST) data from satellites, biases arise due to both measurement and processing error, with a major source of bias coming from uncertainty in the atmospheric state used in the retrieval. If unaccounted for, SST observation biases will propagate through any data assimilation procedure and contaminate the analysis. We have developed a Variational Bias Correction scheme (VarBC) for estimating observation bias in satellite measured SST. In the VarBC system, observation bias is estimated by appending the bias state to the control vector and modifying the observation operator to remove the bias from the observations before comparing to the state.

Information from the innovations is used to estimate both the bias and model state. A term is included in the cost function comparing the bias field to ‘observations-of-bias’. This acts as an additional constraint improving estimates of the bias. In practise, observations-of-bias come from the difference

The RAPID data will be assimilated into a high-resolution (0.25°) global NEMO-CICE model. Assimilating the data using a standard variational procedure with a multi-year time window would be impractical in such a model. Instead, the aim is to use robust covariance information to make earlier increments without the need for an adjoint.

The covariances are used to assimilate the lagged data on top of the trajectory produced by an initial (standard) variational assimilation. Using earlier assimilation increments should give better continuity to the circulation and the heat transports, making the model more useful for coupled forecasting.

We will present the lagged covariance methodology and show results from simulation studies of an idealised system. We will also show the results of the assimilation of RAPID data.

Section 3


Meteorological fields within the ensemble average include 2-meter air temperature, precipitation, and 500-hPa geopotential heights. The original reanalyses were translated onto a common 0.5°x0.5° latitude-longitude grid using bilinear interpolation. In this paper, the merits of each reanalysis model are examined against the ensemble average for the 30-year climate period 1981–2010.

We find that the individual reanalysis models perform similarly, but the ensemble better approximates the observed global average. The four-member reanalysis ensemble can be examined through the website Climate Reanalyzer (http://cci-reanalyzer.org).

An Ensemble Version of the Daily E-OBS Dataset

Author Richard Cornes

Affiliation KNMI

Co-authorsGerard van der Schrier (KNMI), Else van den Besselaar (KNMI), Phil Jones (CRU/UEA)

Daily, gridded datasets formed solely from station data provide an important tool for the evaluation of reanalysis datasets. However, uncertainty in the gridded datasets is rarely taken into consideration in such comparisons, primarily because few gridded datasets provide estimates of uncertainty. In this study we describe a new version of the daily, Europe-wide E-OBS gridded

In order to assess the quality of the climate representation and thereby the added value of regional data sets, we also quantitatively verify the indices derived from reanalyses with independent observations.decadal and multi-decadal timescales

An Ensemble Average and Evaluation of the Third Generation Global Climate Reanalysis

Author Jeffrey D. Auger

Affiliation University of Maine

Co-authorsS. D. Birkel (Climate Change Institute, University of Maine), K. A. Maasch (Climate Change Institute, University of Maine), P. A. Mayewski (Climate Change Institute, University of Maine), K. C. Schuenemann (Metropolitan State University of Denver)

A global ensemble average of monthly output from the four latest-generation climate reanalysis models for the years 1979–2013 is presented here. The models used in this study are ECMWF Reanalysis Interim (ERA-I), NCEP Climate Forecast System Reanalysis (CFSR), JMA 55-year Reanalysis (JRA-55), and NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA). Although each of these models is considered state-of-the-art, an ensemble average can afford a more statistically robust climate signal by smoothing model biases.

permitting model specifications. The analysis is conducted with respect to the representation of near surface point observations for precipitation and wind.

Added value of regional reanalyses: Representation of climate indices

Author Jan D. Keller

Affiliation Hans-Ertel-Centre for Weather Research

Co-authorsS. Wahl (Hans-Ertel-Centre for Weather Reserach, University of Bonn)

The importance of reanalyses as a basis for numerous applications in geosciences, economics and other fields has significantly grown over the last decade. Therefore, a comprehensive evaluation and intercomparison of reanalysis data sets is essential. Here, we quantify the added value of regional atmospheric reanalyses (such as COSMO-REA6) compared to their global forcing reanalysis products (e.g., ERA-Interim, MERRA-2) with respect to monitoring climate and its variability.

To this end, we investigate the representation of climate indices in the reanalyses in comparison to indices derived from observations. The set of climate indices in consideration comprises simple measures such as number of summer days or frost days but also aggregated indices, e.g., heating/cooling degree days.

Section 4 – Evaluation and intercomparisons of reanalyses

Added value of regional reanalyses: Precipitation and wind

Author Sabrina Wahl

Affiliation Hans Ertel Center for Weather Research

Co-authorsJ.D. Keller (Hans Ertel Center for Weather Research, Climate Monitoring Branch)

Regional reanalyses are a rapidly emerging field of research. Such data sets constitute a valuable source of information on smaller spatial scales compared to established global reanalyses. As the production of regional reanalyses requires a high computational effort, the quantification of the added value compared to global reanalyses and/or regional downscaling products is of high interest. In this study we investigate global and regional reanalyses with different horizontal resolutions and model specifications with respect to their near surface representation of wind and precipitation.

Especially for the European domain, several regional reanalysis data sets are available. A comparison with independent observations allows for a quantification of the added value of higher resolutions and/or convection-


valuable, but unique, details that can be used to understand the climate of and biases within the model itself.”

Annual and semiannual cycles of midlatitude near-surface temperature and tropospheric baroclinicity: reanalysis data and AOGCM simulations

Author Valerio Lembo

Affiliation University of Hamburg

Co-authorsI. Bordi (CINFAI), A Speranza (CINFAI)

Seasonal variability in near-surface air temperature and baroclinicity from the ECMWF ERA-Interim (ERAI) reanalysis is analysed in this study. This is compared with a set of six coupled atmosphere–ocean general circulation models (AOGCMs) participating in the Coupled Model Intercomparison Project phase 3 and 5 (CMIP3 and CMIP5).

The annual and semiannual cycles of hemispherically averaged fields are investigated using univariate and bivariate spectral analysis. The aim is to assess the agreement between ERAI and coupled models in the reproduction of the near-surface temperature and baroclinicity annual and semiannual cycles and their coherency and relative phase. Concerning univariate analysis, a statistically significant power spectrum peak is found at the annual frequency in the zonally averaged fields of both hemispheres.

While MERRA-2 indicates that the Arctic Amplification has occurred, a ten member ensemble of the MERRA-2 Atmospheric Model Intercomparison Project (M2AMIP) simulations, using the same prescribed climate forcing, including Sea Surface Temperature (SST) and ice, does not. An evaluation of the temperature tendency within the lower troposphere due to radiation, moisture, and dynamics as well as the surface energy budget in MERRA-2 and M2AMIP will demonstrate that despite identical prescribed SSTs and sea ice in bothversions, enhanced warming in the Arctic and a suppressed warming in the Mid-latitudes in MERRA-2 is in response to the analysis increment tendency due to temperature observations that correct for issues related to inconsistent SST and ice boundary conditions, as presented by Cullather et al.

Furthermore, the implications of the weaker equator-to-pole temperature gradient in M2AMIP on the Mid-latitudes will be discussed through an analysis of variables representing the jetstream, storm tracks, and blocking. Theory suggests an enhanced equator-to-pole temperature gradient will decrease zonal flow in the Mid-latitudes, thereby increasing meridional flow and slowing the progression synoptic systems and it will be demonstrated that this is not necessarily the case in M2AMIP.

Analysis increments from reanalyses as well as a comparison to a free-running version of the model both provide

these NMS datasets compared to the current operational version of the dataset (version 14.0).

The new version of E-OBS is expected to aid evaluation of global-scale reanalyses across Europe, but particularly European-scale regional reanalyses

An Intercomparison of Changes Associated With Earth’s Lower Tropospheric Temperature Using Traditional and AMIP-style Reanalyses

Author Allison B. Collow

Affiliation Universities Space Research Association

Co-authorM.G. Bosilovich (NASA GSFC)

“Reanalyses have become an integral tool for evaluating regional and global climate variations, and even more about the climate and the reanalysis itself can be learned through comparison to identical free-running simulations following the guidelines of the Atmospheric Model Intercomparison Project (AMIP).

Observations and numerous reanalyses, including the Modern Era Retrospective analysis for Research and Applications – Version 2 (MERRA-2), have demonstrated that the Arctic has warmed more rapidly than anywhere else in the world, referred to as “Arctic Amplification”, though uncertainty still remains regarding how this has impacted the Mid-latitudes.

temperature and rainfall dataset that contains a number of significant developments over earlier releases.

Notably, uncertainty estimates are generated from a 100-member ensemble of realizations of each daily gridded field. In order to produce a consistent ensemble of realizations, the original interpolation method used in E-OBS has been overhauled. In contrast to the kriging/spline method used in earlier versions, we have made use of Generalized Additive Modelling. Topographic effects are integrated through the modelling of gridded background fields that are calculated using month-by-month climatological averages calculated over the period 1961-90.

In addition to altitude, these background fields also incorporate additional environmental factors, such as coastal proximity and slope/aspect. To assess the success of the new interpolation method, the gridded data are compared against several high-resolution gridded datasets produced by National Meteorological Services (NMS) across Europe.

These datasets generally contain many more station data and are therefore expected to replicate the true daily fields of temperature or precipitation more accurately than E-OBS, but do so at a scale that is comparable to E-OBS. On the whole the new version of E-OBS has reduced error relative to

Section 4


Assessment of MERRA-2 Land Surface Energy Flux Estimates

Author Rolf H. Reichle

Affiliation NASA/GSFC

Co-authorsC. S. Draper (NASA/GSFC and NOAA ESRL/CIRES), R. D. Koster (NASA/GSFC)

In NASA’s Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis the land is forced by replacing the model-generated precipitation with observed precipitation before it reaches the surface. We assess the MERRA-2land surface energy fluxes and 2 m air temperatures (T2m) and investigate whether the inserted precipitation observations result in the expected improvements to these fields. Averaged over global land, MERRA-2 overestimates the latent heat (LH) and incoming shortwave radiation (by 5-10 W/m2) and underestimates (in magnitude) the incoming and outgoing longwave radiation (by 10-15 W/m2), while the sensible heat biases are unclear.

The global average biases differ only slightly from those in NASA’s previous reanalysis, MERRA. In regions where LH is limited by surface moisture availability and hence sensitive to local precipitation, the MERRA-2 LH biases are reduced from those in MERRA, and the direction of change is consistent with the precipitation increments from inserting

system of the region that is characterized by strong coastal upwelling and one of the driest regions on Earth land inwards, i.e. the Atacama desert.

Within the German Science Foundation funded Collaborative Research Center “Earth at its dry limit” our overarching goal is to understand the moisture supply to the Atacama desert and its variability which is to a large degree affected by stratocumulus clouds moving inland. Reanalyses such as ERA-Interim and ERA-20C are well suited to study trends and variability in cloud geometry with respect to interannual and interdecadal patterns such as El Niño Southern Oscillation or Pacific Decadal Oscillation.

In order to further assess the quality of the reanalyses, a comparison to satellite retrievals from Multi-angle Imaging SpectroRadiometer (MISR) on Terra is carried out. In addition, to the more traditional parameters cloud fraction and cloud top height a novel approach enables us to derive CBHs with a horizontal resolution of 0.25°x0.25°. Previous research shows a good agreement of these observations with ceilometer measurements within a continental region of the USA. Here, this new approach is applied to an area within the stratocumulus region of the Southeast Pacific over a time period of 16 years between 2001 and 2016. Furthermore, regional and seasonal variabilities of cloud heights are investigated.

Assessment of cloud geometry in ERA-Interim and ERA-20C over the Southeast Pacific using satellite observations

Author Christoph Böhm

Affiliation University of Cologne

Co-authorsSusanne Crewell (Institute of Geophysics and Meteorology, University of Cologne, Germany), Ulrich Löhnert (Institute of Geophysics and Meteorology, University of Cologne, Germany), Johannes Quaas (Institute for Meteorology, University of Leipzig, Germany), Odran Sourdeval (Institute for Meteorology, University of Leipzig, Germany), Johannes Mülmenstädt (Institute for Meteorology, University of Leipzig, Germany)

The representation of clouds in climate models is still subject to large uncertainties. In particular this holds true for marine boundary layer clouds. As the Earth’s radiation budget is strongly influenced by clouds, these uncertainties introduce a wide spread among simulations of future temperature increase. Important parameters which affect the net radiative effect of clouds are cloud cover along with cloud top and cloud base height (CBH).

In this study, we focus on the Southeast Pacific which hosts the largest subtropical stratocumulus deck on Earth. The associated stratocumulus clouds represent a critical but poorly understood component of the coupled climate

The semiannual peak, instead, shows less power and in the NH seems to have a more regional character, being observed in the North Pacific Ocean region. Bivariate analysis for such a region and the whole Southern Hemisphere midlatitudes shows some discrepancies between ERAI and model data, as well as among models, especially regarding the semiannual frequency. Specifically, (i) models and ERAI agree on the coherency at the annual and semiannual frequency in both hemispheres, and (ii) on the annual frequency, showing a relative phase of 220±15°.

The latter denotes an approximately 1-month phase shift between temperatures and baroclinicity annual cycle. At the semiannual frequency model phases show a wider dispersion in both hemispheres with larger errors in the estimates, denoting increased uncertainty and some disagreement among models and with ERAI. We believe that better constraining the cyclic response of current global atmosphere–ocean models to the external (solar) forcing might be helpful for the improvement of seasonal forecasts.

Section 4


and Remote Sensing Center, Norway), K. Andrew Peterson (Met Office, UK), Steffen Tietsche (European Centre for Medium-Range Weather Forecasts), Li Shi (Bureau of Meteorology, Australia), Zhaoru Zhang (Shanghai Jiao Tong University), Remon Sadikhi (University of Hamburg)

Ocean reanalysis (ORA) combines observations either statistically or with a hydrodynamical model, to reconstruct historical changes in the ocean. Global and regional ORA products are increasingly used in polar research, but their quality remains to be systematically assessed. To address this, the Polar ORA Intercomparison Project (PORA-IP) has been established following on from the ORA-IP project (Balmaseda et al. 2015, with other papers in a special issue of Climate Dynamics).

The PORA-IP is constituted under the COST EOS initiative with plans to review reanalyses products in both the Arctic and Antarctic, and is endorsed by YOPP – the Year of Polar Prediction project. Currently, the PORA-IP team consists of 23 researchers from 16 institutes and universities. The ORA-IP products with polar physics, such as sea ice, have been updated where necessary and collected in a public database.

In addition to model output, available observational polar climatologies are collected and used in the assessments. Due to the extensive variety of products, this database should become a valuable resource outside the PORA-IP community. For a comprehensive

Summary statistics from the observed records and the gridpoint series from low-resolution reanalysis products and corresponding high-resolution dynamical downscaling were compared over the period from 1979 to the last decade.

Assessment of ten ocean reanalyses in the polar regions

Author Dorotea Iovino

Affiliation CMCC

Co-authorsPetteri Uotila (Finnish Meteorological Institute), Marika Marnela (Finnish Meteorological Institute), Meri Korhonen (Finnish Meteorological Institute), Antoine Barthélemy (Université catholique de Louvain), Hugues Goosse (Université catholique de Louvain), François Massonnet (Université catholique de Louvain, Belgium and Barcelona Supercomputing Centre, Spain), James Carton (University of Maryland), Keith Haines (University of Reading, UK), Davi Mignac Carneiro (University of Reading, UK), Frank Kauker (Alfred Wegener Institute, Germany), Matthieu Chevallier (Centre National de Recherches Météorologiques, Météo France/CNRS UMR3589, France), Marie Drevillon (Mercator Océan, France), Gilles Garric (Mercator Océan, France), Clement Bricaud (Mercator Océan, France), Neven Fuckar (Barcelona Supercomputing Centre, Spain), Vidar Lien (Institute of Marine Research, Norway), Jiping Xie (Nansen Environmental

severe impacts on the society and the environment. Nonetheless, systematic biases and uncertainties can affect the ability of reanalysis system in describing the true state of climate, specially at the local scale.

The Italian Peninsula with its complex topography can be regarded as an interesting test for assessing reanalysis representation of climatic extremes. We took advantage of the availability of a new dataset of high-quality, land-based precipitation records of observations to compare and evaluate the capability of low-resolution global reanalysis products and numerical high-resolution CORDEX simulations in reproducing precipitation extreme events over Italy.

In particular, the Med-CORDEX simulations driven by ERA-Interim will be taken into account. The observation series was retrieved from the national system of climate data SCIA and covers almost uniformly the country. The series were selected in order to meet severe completeness and continuity requirements. Potentially inhomogeneous records at yearly level were discarded. First, a number of contiguous subregions were identified using hierarchical cluster analysis based on daily observations of precipitations.

Then the spatial and temporal occurrence of moderate extreme rainfall events in each cluster was investigated through the calculation of a subset of indices from the Expert Team on Climate Change Detection and Indices (ETCCDI).

the observed precipitation. However, large positive biases remain in some regions where LH is not moisture-limited.

The globally averaged anomaly correlations (Ranom) with reference data were improved from MERRA toMERRA-2, for both LH (from 0.40 to 0.50 vs. GLEAM data) and the daily maximum T2m in Boreal summer (from 0.64 to 0.70, vs. CRU data). There is a strong correspondence between regions of the greatest improvement in the MERRA-2 T2m Ranom, and regions where the MERRA-2 T2m is most sensitive to the inserted observed precipitation, suggesting that the observed precipitation did in fact lead to improved T2m.

Assessment of reanalysis precipitation extremes over Italy from global reanalysis products, high-resolution simulations and historical observations

Author Emanuela Piervitali

Affiliation Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA)

Co-authorsG. Fioravanti (ISPRA), A. Dell’Aquila (ENEA), S. Calmanti (ENEA), F. Desiato (ISPRA), E. Piervitali (ISPRA)

Reanalysis gridded datasets are a valuable source of information for monitoring climate variability and change and assessing the evolution of climate extremes, which can have

Section 4


a suppression of high frequency variability is apparent in the centennial reanalysis products.

This behaviour does not have a counterpart in the atmospheric model integrations. Since the latter differ from one of the reanalysis products considered here (ERA-20C) only in the assimilation of surface observations, it seems reasonable to attribute the high frequency variability suppression to the poor coverage of the observations assimilated.

Biases in the 20th Century Reanalysis Version 2c

Author Laura C. Slivinski

Affiliation Univ. of Colorado’s Cooperative Institute for Research in Environmental Sciences

Co-authorsG.P. Compo (CIRES/NOAA), J.S. Whitaker (NOAA), P.D. Sardeshmukh (CIRES/NOAA)

The NOAA-CIRES Twentieth Century Reanalysis version 2c (20CRv2c) was publicly released in 2015, and included many improvements over the previous version 2 system. However, several biases and issues in version 2c remain. First, version 2c used a digital filter in its 6 hour first guess fields to damp gravity waves that can cause numerical instabilities. This filter generated artificial trends in precipitation that can be seen in the forecast fields: the hour 3-6

Benchmarking Northern Hemisphere midlatitude atmospheric synoptic variability in centennial reanalysis and numerical simulations

Author Alessandro Dell’Aquila

Affiliation ENEA

Co-authorsSusanna Corti (ISAC-CNR), Antje Weisheimer (ECMWF, Uni. Oxford), Hans Hersbach (ECMWF), Carol Peubey (ECMWF), Paul Poli (ECMWF, MeteoFrance), Paul Berrisford (ECMWF), Dick Dee (ECMWF), Adrian Simmons (ECMWF)

The representation of midlatitude winter atmospheric synoptic variability in centennial reanalysis products, which assimilate surface observations only, and atmospheric model simulations constrained by observation-based datasets is assessed. Midlatitude waves activity in twentieth century reanalyses (20CR, ERA-20C) and atmospheric model simulations (AMIP ERA-CLIM) are compared with those estimated from observationally-complete reanalysis products.

All reanalyses are in good agreement regarding the representation of the synoptic variability during the last decades of the twentieth century. This suggests that the assimilation of surface observations can generate high-quality extratropical upper-air fields. In the first decades of the twentieth century

Assessment of the Conventional Observation Reanalysis (CORe)

Author Li Zhang

Affiliation INNOVIM/CPC/NOAA

Co-authorsArun Kumar (CPC/NCEP/NOAA), Jeffrey Whitaker (PSD/NOAA), Jack Woollen (IMSG), Wesley Ebisuzaki (CPC/NCEP/NOAA), Hyun-Chul Lee (EMC/NOAA)

The Conventional Observation data based EnKF (Ensemble Kalman Filter) atmospheric reanalysis (CORe) was recently completed at the National Centers for Environmental Prediction (NCEP), for the period of 1950 to 2010. The observations assimilated include surface station data, radiosondes and pibals, profilers, aircraft data, and satellite winds. The EnKF system is based on the latest Semi-Lagrangian Global Forecast System (GFS) T254 L64 model.

By not assimilating satellite radiances, CORe avoids the spurious climate shifts caused by introduction of new satellites. However, one expects a larger lossof accuracy in regions where the conventional observation network is weak such as the Southern Hemisphere and above the tropopause.

This initial assessment focuses on the monthly up to the decadal variability for a set of surface and tropospheric variables. The results are compared with other available reanalyses (R1, CFSR, JRA55c, ERAI and MERRA2).

evaluation of the ten ORA products (CGLORSv5, ECDA3.1, GECCO2, Glorys2v4, GloSea5_GO5, MOVEG2i, ORAP5, SODA3.3.1, TOPAZ4 and UR025.4) in the Arctic and Southern Oceans several specific diagnostics are assessed.

The PORA-IP diagnostics target the following topics: hydrography; heat, salinity and freshwater content; ocean transports and surface currents; mixed layer depth; sea-ice concentration and thickness; and snow thickness over sea ice. Based on these diagnostics, ORA product biases against observed data and their mutual spread are quantified, and possible reasons for discrepancies discussed.

So far, we have identified product outliers and evaluated the multi-model mean. We have identified the importance of the atmospheric forcing, air-ocean coupling protocol and sea-ice data assimilation for the product performance. Moreover, we are investigating co-variability between the Arctic Ocean heat content and the North Atlantic heat transport, and between the mixed layer depth, oceanic convection, the upper ocean hydrography and sea ice.

We will also present other diagnostic results which provide closely related information for those interested in enhancing model predictive skill over a range of time scales, including seasonal to decadal.

Section 4


Characterisation of Air-Sea Fluxes from Reanalysis Products over the Bay of Bengal during the Southwest Monsoon

Author Alejandra Sanchez-Franks

Affiliation National Oceanography Centre

Co-authorsE.C. Kent (National Oceanography Centre, Southampton, UK), A.J. Matthews (Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences and School of Mathematics, University of East Anglia, Norwich, UK), B.G.M. Webber (Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences and School of Mathematics, University of East Anglia, Norwich, UK), S.C. Peatman (National Centre for Atmospheric Science, Climate and Department of Meteorology, University of Reading, UK), P.N. Vinayachandran (Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore, India).

Meteorological variables and surface flux variables from five reanalysis products are compared and evaluated against in-situ data from the RAMA moored array.

The reanalysis products, ERA-Interim (ERA-I), TropFlux, MERRA2, JRA-55 and CFSR are specifically assessed for their characterisation of air-sea fluxes during the southwest monsoon season (JJAS) in the Bay of Bengal. Results

The radiosonde data show only small variations and weak trends in tropospheric RH over China. Using these homogenized observations, the PW from the NCEP/NCAR, NCEP/DOE, MERRA, JRA-55, JRA-25, ERA-Interim, ERA-40, CFSR and 20CR reanalyses is evaluated for the period from 1979-2012 (1970-2001 for ERA-40).

Results suggest that the PW biases in the reanalyses are within ~20% for most of northern and eastern China, but the reanalyses underestimate the observed PW by 20%–40% over western China, and by ~60% over the southwestern Tibetan Plateau. The newer-generation reanalyses (e.g., JRA25, JRA55, CFSR and ERA-Interim) have smaller root-mean-square error (RMSE) than the older-generation ones (NCEP/NCAR NCEP/DOE and ERA-40). Most of the reanalyses reproduce well the observed PW climatology and interannual variations over China.

However, few reanalyses capture the observed long-term PW changes, primarily because they show spurious wet biases before about 2002. This deficiency results mainly from the discontinuities contained in reanalysis RH fields in the mid-lower troposphere due to the wet bias in older radiosonde records that are assimilated into the reanalyses. Thus, more efforts are needed to remove spurious changes in input data for future long-term reanlayses.

for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, China)

Radiosonde humidity data provide the longest record for assessing changes in atmospheric water vapor, but they often contain large discontinuities because of changes in instrumentation and observational practices.

In this study, the variations and trends in tropospheric humidity (up to 300 hPa) over China are analyzed using a newly homogenized radiosonde dataset. There are, however, many spurious changes and discontinuities in the raw radiosonde records resulting from changes in instruments, observational practice, processing procedures, station relocations, and other issues. Recently, the daily humidity records radiosonde derived from about 130 Chinese stations were homogenized using a new approach developed by Dai et al. (2011).

It is shown that the homogenization removes the large shifts in the original records of humidity resulting from sonde changes in recent years in China, and it improves correlation of the precipitable water (PW) with precipitation and the spatial coherence of the PW trend during recent 40 years. The PW variations and changes are highly correlated with those in lower–midtropospheric mean temperature (r = 0.83), with a dPW/dT slope of ~7.6% K−1, which is slightly higher than the 7% K−1 implied by Clausius–Clapeyron equation with a constant relative humidity (RH).

precipitation forecasts are consistently and significantly larger than the hour 0-3 forecasts. Second, version 2c did not include bias correction to marine observations.

In the 19th century, these observations were strongly biased, and have been shown to significantly impact the global sea level pressure in this time period. Finally, 20CRv2c has an apparent high-pressure bias over the high Southern latitudes in the early-to-mid 20th century. Potential reasons for this include a possible model bias, lack of observations in this region at this time, and nonlinear interactions with the data assimilation system. Many of these issues are being addressed in the new 20CR version 3 system currently in development.

Changes of atmospheric precipitable water in observations and reanalysis over China

Author Tianbao Zhao

Affiliation Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS)

Co-authorsJingpeng Zhang (Key Laboratory of Regional Climate-Environment Research for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, China), Tianbao Zhao (Key Laboratory of Regional Climate-Environment Research

Section 4


2016. Results and data sets gathered during the four IOPs allowed us to contrast diverse reanalysis products such as Era-Interim, MERRA-2, NCEP/NCAR and CFSR. Preliminary results show striking cold and wet mid-troposphere biases in the reanalysis over both ocean and land.

This effect is likely related with colder radiative effect of smoothed terrain constrained to the reanalysis resolution and dispersion of these errors over the regional ocean by the predominant mid-tropospheric easterly flow. However, some noisier but warmer and drier biases are observed during organised convective activity episodes. Such disturbed convective environments appear to be unresolved by all reanalysis products, even by those assimilating satellite data. Although there are not significant differences regarding the different reanalysis, NCEP/NCAR (the coarser reanalysis) shows the largest biases, overestimating temperature around 5°C at mid-to-upper levels.

for evaluating the reanalysis skills to capture and display regional and local atmospheric circulations.

The CHOCO-JEX experiment is an on-going international and inter-institutional research program developed by Universidad Nacional de Colombia at Medellín, the General Maritime Directorate of the Colombian Navy, the Colombian Air Force, and the Desert Research Institute at Reno, Nevada, US.

The main objective of CHOCO-JEX is to expand our understanding of the tropospheric flow characteristics of the Choco Jet through observations, assimilation and reanalysis. To that end, four 8-day Intensive Observation Periods (IPO) have taken place, two over land and two over the Pacific off the coast of Colombia, including the deployment of upper-air soundings to monitor the predominant diurnal cycles patterns (4 times per day) and the seasonal variability. The maritime IOPs took place during January and November 2016 on board of the ARC Gorgona vessel.

Such campaigns were constrained by the availability of the research vessel, whose schedule was tied to the near yearly reconnaissance marine campaigns aiming to monitoring El Niño/Southern Oscillation (ENSO) over the Colombian coastal waters making part of the Estudio Regional del Fenómeno de El Niño (ERFEN). The continental component of the CHOCO-JEX IOPs was carried out in the city of Quibdó (5°41′32″N, 76°39′29″W) during June and October

CHOCO-JEX: A Research Programme Focused on the CHOCO Low-level Jet over the Far Eastern Pacific and Western Colombia – Reanalysis Evaluation

Author Johanna Yepes

Affiliation Universidad Nacional de Colombia

Co-authorsGermán Poveda (Departamento de Geociencias y Medio Ambiente, Universidad Nacional de Colombia, Sede Medellín, Facultad de Minas, Medellín, Colombia), John F. Mejía (Desert Research Institute, Reno, NV, United States), Leswis Cabeza (Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico, Tumaco, Colombia), Carolina Rueda (Subdirección de Meteorología, Fuerza Aérea Colombiana, Bogotá, Colombia)

The Choco Low-Level Jet (Choco Jet) has been related to the formation of large and frequent Mesoscale Convective Systems over the far eastern Pacific Ocean and inland over the world-record rainy region of western Colombia. The structure and dynamic of the Choco Jet have been studied using reanalysis products, but no permanent upper-air soundings have been put in place on the region neither for improving the understanding of the Choco Jet nor

show that TropFlux and (to a slightly lesser extent) ERA-I perform best, with the highest correlations and smallest biases when compared to the observed meteorological parameters and the associated fluxes from the RAMA array.

In contrast, MERRA2, CFSR and JRA-55 have lower correlations and much higher biases when compared to the observed data. In general, however, all products struggle to capture shortwave radiation flux (SWR) and latent heat flux (LHF), with non-negligible biases ranging from -6 W/m2 to 75 W/m2. Further analysis of the flux variables showed SWR and LHF to be the largest drivers of the observed net heat flux variability, thus highlighting the importance of the results from the reanalysis product comparison to the RAMA buoy.

It was also found that mean fields were consistent with the findings at the buoy location, indicating confidence in the representation of variability across the basin. Finally, the representation of the intraseasonal variability was investigated through the boreal summer intraseasonal oscillation and it was shown that TropFlux and ERA-I perform best at capturing intraseasonal climate variability during the southwest monsoon season.

Section 4


To achieve this, cyclone and windstorm time series are low-pass filtered with a cut-off frequency of 1/31 years and high frequency variability is assessed by calculating the remainder between original and low-pass filtered time series. The results suggest partly large differences w.r.t. long-term trends of both extra-tropical cyclones and windstorms, most pronounced during the early 20th century. Interestingly, a better agreement is found for high-frequency variability, especially over the Northern Hemisphere. The outcome of this study suggests that it is difficult to draw reliable information about long-term variability of extra-tropical cyclone and windstorm events during the past century from these two reanalysis datasets. In contrast, studies focusing on short-term variability of these events might be useful if long-term trends are taken into account.

In the stratosphere the temperature time series relationship R1 and R2 with R3 considerably less, especially over the oceans. So, on the 100 hPa in January over the oceans the correlation is close to zero.

Comparison of Extra-tropical Cyclones and Windstorms in ERA-20C and NOAA-20CR Reanalyses

Author Daniel J. Befort

Affiliation University of Birmingham

Co-authorsS. Wild (University of Birmingham, School of Geography, Earth and Environmental Sciences, Birmingham, United Kingdom), T. Kruschke (GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany), U. Ulbrich (Institute of Meteorology, Freie Universität Berlin, Germany), G.C. Leckebusch (University of Birmingham, School of Geography, Earth and Environmental Sciences, Birmingham, United Kingdom)

Extra-tropical cyclones and windstorms over both hemispheres are analysed for the 20th century in two reanalysis datasets, ERA-20C and NOAA-20CR (v2) (Befort et al., 2016). Analyses focus on long and short-term variability of these events as knowledge on the variability on different time-scales is of high importance due to their damage-related impact.

While in the winter and summer seasons these distinctions have a significant difference both in magnitude and sign. There is also a non-linear character of the investigated period differences in air temperature. This particularly evident in the Middle troposphere, where at the beginning of the period the difference grows to a value of 0.8°C. Further, since the second half of the 1980s and until the beginning of the 21 century, the difference goes to zero, and then grows again.

At the end of the period the temperature difference, submitted by reanalyses R1 and R3, reaching values of 0.4°C. Non-linear course of temperature difference is also reflected in the respective coefficients of linear temperature trends. In the same time sign of linear trend coefficient does not change. In General, in the troposphere according to all reanalyses holds temperature rise. Unlike the troposphere, in the tropopause region and lower stratosphere temperature trend reversal is observed.

According to the R1 and R2 on the surfaces of 200 and 100 hPa temperature decreases, but according to R3 temperature changes are not statistically significant. In the middle stratosphere (30 and 10 hPa) according to all reanalyses temperature decreases.

The calculation of the coefficients of the linear correlation between the time series of temperature according to the R1, R2 and R3 showed that in the troposphere, the correlation is great (more than 0.9).

Comparative evaluation of the changes of the temperature in the troposphere and stratosphere of the Northern Hemisphere according to reanalyses NCEP and ERA-Interim

Author Vladimir V. Guryanov

Affiliation Kazan Federal University

Co-authorsK.M. Shantalinskiy (Kazan Federal University), Yu.P. Perevedentsev (Kazan Federal University)

According to the three reanalyses NCEP-NCAR1, NCEP-DOE2 and ERA-Interim (next, respectively, R1, R2 and R3) evaluated differences in air temperature in the free atmosphere averaged on the Northern Hemisphere. The nature of the impact of these differences on the assessment of changes of air temperature during the period 1979-2013 is defined. Found that reanalysis R2 and R3 are more equal temperatures compared to R1.

The studies were identified differences in dependence of reanalysis from the ocean and land. In the lower troposphere over the oceans R3 gives lower values of air temperature compared to R2 and more so with R1 (average for the year to 1.2°C). Over land temperature difference is not significant.

Section 4


we investigate how the results differ, with special focus on wind fields. The 10m-windspeed and also wind speed for several model heights up to 100m are compared with station and mast observations. ERA-Interim is added in the comparison as a benchmark.

Mean square error, bias, correlation and other skill scores are investigated to quantify the differences in the four reanalyses depending on local and temporal scale. In general, the synoptic patterns are captured well by all regional reanalysis productions. There are examples for each regional reanalysis outperforming the other ones at certain locations.

For special case studies, the comparison with independent or dependent wind observations could hint on abilities and limitations of each reanalysis system, which has to be investigated further. Here we give a first assessment of uncertainties in UERRA’s regional reanalyses with the intention to guide potential users.

a decrease of performance for others. This work can thus help choosing an appropriate dataset for the analogue method considered, or raise awareness of the consequences of using a certain dataset.

Comparison of wind fields from European regional reanalyses from the UERRA project and COSMO-REA6

Author Deborah Niermann


Co-authorsAndrea K. Kaiser-Weiss (Deutscher Wetterdienst), Michael Borsche (Deutscher Wetterdienst), Frank Kaspar (Deutscher Wetterdienst)

Within the FP7 project UERRA (Uncertainties in Ensembles of Regional ReAnalyses) several new large data sets are produced, mainly for the European CORDEX domain. At their boundary, these regional reanalyses are driven similarly by ERA-Interim (and ERA-40 for years before 1979). The various regional reanalyses employ different regional models: UM by UKMO, HARMONIE by SMHI, MESCAN by MeteoFrance and COSMO by DWD.

Their data assimilation systems range from nudging of conventional observations (DWD), optimal interpolation for surface observations (MeteoFrance), 3D-Var for the full observing system (SMHI) to 4D-Var for UKMO. Here

products are available nowadays that differ in terms of assimilation technique, assimilated data, atmospheric model, archive length, and spatial and temporal resolution.

The context of the application of analogue methods might drive the choice of an appropriate dataset, for example when the archive length is a leading criterion. However, in many studies, a reanalysis dataset is subjectively chosen, according to the user’s preferences or the ease of access. The impact of this choice on the results of the downscaling procedure is rarely considered and no comprehensive comparison has been undertaken so far. In order to assess the impact of the archive’s quality in the analogue method, ten global reanalysis datasets were compared in seven versions of the analogue method, over 300 precipitation stations in Switzerland.

Despite the fact that all reanalysis datasets might be considered accurate for central Europe, differences in terms of prediction performance were identified. Satellite-based products generally showed higher skills. There were no overall winner amongst these, but some datasets were found to perform better for different methods. MERRA-2 provides SLP data particularly skillful in the analogue method. Geopotential heights from CFSR show slightly higher skills, as well as the vertical velocity from JRA-55. Increasing the complexity of the analogue method was relevant only for certain datasets, while it led to

Comparison of ten global reanalysis datasets for precipitation prediction with a statistical downscaling method

Author Pascal Horton


Co-authorsRolf Weingartner (Oeschger Centre for Climate Change Research, Institute of Geography, University of Bern, Switzerland), Stefan Brönnimann (Oeschger Centre for Climate Change Research, Institute of Geography, University of Bern, Switzerland), Charles Obled (Laboratoire d’étude des Transferts en Hydrologie et Environnement, LTHE, Université de Grenoble-Alpes, Grenoble, France)

The analogue method allows predicting precipitation by means of a statistical downscaling of synoptic predictors. To predict the precipitation for a target day of interest, analogue days are sought in long archives of synoptic predictors, typically from reanalysis datasets.

A certain number of analogue days are then extracted and their corresponding observed precipitation is used to establish a conditional empirical distribution, which is the statistical prediction for the target day. Most of the recent analogue methods rely on the atmospheric circulation as the main predictor, with additional predictors based on moisture, air temperature, and vertical velocity. Many different reanalysis

Section 4


existing ones. The simulations were performed for January 2010. The chosen parameterizations will be applied for long term 2010-2015 hindcast.

Duration and Decay of Extreme Vortex Events in the Polar Stratosphere: Comparison of the ECMWF Seasonal Forecast Model with Reanalyses

Author Yvan Orsolini

Affiliation NILU – Norwegian Institute for Air Research

Co-authorsKazuaki Nishii (Mie University), Hisashi Nakamura (University of Tokyo)

We investigate extreme stratospheric polar vortex events in the operational seasonal forecast model (System 4) of the European Centre for Medium-Range Forecasting (ECMWF) in comparison to re-analysis data during the Northern Hemisphere winter. While previous studies have documented both weak vortex events (WVE) and strong vortex events (SVE) in models or re-analyses, there has been little focus on the duration of these events and their decay processes.

To this end, we use a 5-member set of 7-month reforecasts made over the period 1981-2014, and compare with the Japanese 55-year Reanalysis (JRA-55) dataset. Strong and weak vortex events are classified into short (less

Parameters such as: surface pressure, relative humidity, 2-m air temperature and 10-m wind speed have been simulated for the purpose of further implementation in fjord –ocean water circulation, hydrodynamic model. Special emphasis was put on obtaining proper wind conditions.

Results from simulations with different reanalysis data sets used for the boundary condition: ECMWF – Era Interim and NCEP – Climate Forecast System Reanalysis (CFSR) have been compared. The results have been validated against observations performed in the Polish Polar Station in Hornsund and measurements conducted in the Bayelva/Ny-Ålesund in Norwegian synoptic station. Preliminary results show good agreement with 2-m temperature, relative humidity, surface pressure. However results show high bias associated with higher wind speeds.

For the sake of large wind impact on the water circulation in fjord, especially due to the phenomena of “topography tunnelling” along the fjord axis, further studies have been performed considering specially attention on the wind field. The problem has been diagnosed as a bad representation of subgrid-scale orographic effects.

Therefore the dedicated parameterizations have been applied. The presentation points up the problem of lack of topographic data for Arctic regions and unreliability of

throughout the model simulation. Therefore, the system can be utilized with a deterministic forcing at the lateral boundaries.

Here, the system is used for the production of a 21 member ensemble for an initial 5 year time period. In this presentation, we focus on the evaluation of the quality of the data set using basic diagnostics for observations and data assimilation monitoring as well as on the probabilistic evaluation using standard measures for ensemble reliability and/or resolution, e.g. spread-skill relation, rank histograms, Brier/CRPS scores.

The provided uncertainties are also evaluated by comparison against other ensemble reanalyses produced within UERRA.

Customizing the Weather Research and Forecasting Model for west Spitsbergen fjords – wind hindcast

Author Szymon Kosecki

Affiliation Centre for Polar Studies

Co-authorsK.S.A. Kjetil Schanke Aas University of Oslo, J.J. Jaromir Jakacki, L.D.G. Lidia Dzierzbicka-Głowacka

The state-of-the-art Weather Research and Forecasting Model has been applied for the West Spitsbergen fjords: Hornsund and Kongsfjorden.

COSMO ensemble reanalysis system for Europe: diagnostics of quality of data assimilation and uncertainty estimates

Author Maarit Lockhoff

Affiliation University of Bonn

Co-authorsM. Borsche (Deutscher Wetterdienst), L. Bach (Deutscher Wetterdienst), C. Schraff (Deutscher Wetterdienst), K. Stephan (Deutscher Wetterdienst), J. Keller (Deutscher Wetterdienst)

The objective of the FP-7 funded project Uncertainties in Ensembles of Regional Reanalyses (UERRA) is to produce ensembles of European regional atmospheric reanalyses of Essential Climate Variables thereby providing estimates for the associated uncertainties in the data sets. One of these data sets is the high resolution probabilistic COSMO-EN-REA12 reanalysis (Bach et al. 2016) which is based on the non-hydrostatic limited-area model COSMO (COnsortium for Small-scale MOdeling). It is produced at 12-km grid spacing and with hourly resolution covering the CORDEX-EUR11 domain. The applied ensemble data assimilation method is an ensemble nudging scheme. In this scheme, an ensemble of different deterministic nudging realizations is generated by perturbing the observations with perturbations reflecting the observation errors. A major benefit of this approach is that uncertainty is generated

Section 4


Snow cover variability has significant effects onlocal and global climate evolution. By changing surface en-ergy fluxes and hydrological conditions, changes in snowcover can alter atmospheric circulation and lead to remoteclimate effects. To document such multi-scale climate ef-fects, atmospheric reanalysis and derived products offer theopportunity to analyze snow variability in great detail farback to the early 20th century.

So far only little is know abouttheir quality. Comparing snow depth in four long-term re-analysis datasets with Russian in situ snow depth data, wefind a moderately high daily correlation (around 0.6–0.7), which is comparable to correlations for the recent era (1981–2010), and a good representation of sub-decadal variability. However, the representation of pre-1950 inter-decadal snowvariability is questionable, since reanalysis products diverttowards different base states.

Limited availability of indepen-dent long-term snow data makes it difficult to assess the exactcause for this bifurcation in snow states, but initial investiga-tions point towards representation of the atmosphere rather than differences in assimilated data or snow schemes. Thisstudy demonstrates the ability of long-term reanalysis to re-produce snow variability accordingly.

The impact of aerosols, as evidenced by the sensitivity experiments with ECHAM5-HAM, sets up an inter-hemispheric gradient in the TOA and surface budget after 1960, increasing the total poleward transport in the Northern Hemisphere and decreasing it in the Southern Hemisphere. This feature is not found in ERA-20CM, suggesting a substantial difference in the representation of the aerosol forcing in the two experiments.

SST variations do not seem to induce long-term variations in the patterns of TOA budget and related total meridional transport. On the contrary most of the surface and atmospheric budget and transport inter-annual variability is attributable to the evolution of SST, and much more agreement is observed among the two models in this respect.

Eurasian snow depth in long-term climate reanalyses

Author Martin Wegmann

Affiliation University of Grenoble

Co-authorsYvan Orsolini (NILU), Olga Bulygina (All-Russian Research Institute of Hydrometeorological Information – World Data Centre), Alexander Sterin (All-Russian Research Institute of Hydrometeorological Information – World Data Centre), Stefan Brönnimann (University of Bern)

Energy budgets and transports: global evolution and spatial patterns during the twentieth century as estimated in two AMIP‐like experiments

Author Valerio Lembo

Affiliation University of Hamburg

Co-authorsD. Folini (ETH Zürich), M. Wild (ETH Zürich), P. Lionello (Università del Salento)

The 20th century evolution and spatial patterns of the Top-of-Atmosphere (TOA), atmospheric, and surface energy budgets (EB) are investigated in this work. Total, atmospheric and oceanic meridional energy transports are also computed from the EBs.

Two AMIP-like ensemble simulations are considered: Integrated Forecast System (IFS) simulations of the ERA-20CM experiment, and ECHAM5-HAM model simulations. With the latter, additional sensitivity experiments are carried out by constraining either Sea-Surface Temperatures (SST) and Sea-Ice Cover (SIC) or aerosol concentrations to climatological values.

The recent decades estimates of the EB are in reasonable agreement in the two models, while they are not for what concerns the global scale evolution. Particularly, in the 1970s ERA-20CM shows a fast transition from negative to positive EBs at Top of Atmosphere (TOA) that is not found in ECHAM5-HAM.

than 10 days) and long (no less than 20 days) events, and each category is composited.

In particular, we examine how the characteristics of each category (i.e. frequency of occurrence, anomalous winds and E-P fluxes) are represented in the forecast model in comparison to the reanalyses. Obviously, long WVEs (SVEs) tend to be accompanied by longer enhancement (suppression) of upward-propagating planetary wave than their short counterparts. Both types begin in the same fashion with a barotropic zonal wind anomaly extending from 1 hPa to the lower stratosphere, but in the latter case, sustained wave forcing from the upper-troposphere allows for persistence and further downward propagation of the wind anomalies.

However, short WVEs uniquely show an E-P flux divergence anomaly dominated by its meridional component in their ending phase, which suggests that barotropic instability abruptly terminates these events. The characteristics of precursory upper-tropospheric disturbances are also examined for each category, in both the seasonal forecast model and the reanalyses.

Section 4


added value of the regional reanalyses compared to existing global reanalyses, the global radiation of ERA-Interim is included into this study.

Evaluating groundwater resources by means of global datasets

Author Paolina Bongioannini Cerlini

Affiliation Centre for Climate and Climate Change, University of Perugia

Co-authorsS. Meniconi (Centre for Climate and Climate Change, University of Perugia), B. Brunone (Centre for Climate and Climate Change, University of Perugia)

Climate change influences the hydrological cycle with direct effects on groundwater resources, one of the most important supply source for human consumption and irrigation. In the framework of assessing water balance and the related hydraulic works for water supply, it is crucial to correlate quantitatively climate trends, precipitation and groundwater behaviour. In this paper, the use of global atmospheric datasets as a reliable tool for water resources management is further explored.

In fact, in a previous paper (Cerlini et al., 2017), ERA-Interim reanalysis of meteorological observations made by the European Centre for Medium-Range Weather Forecasts (ECMWF) have

reanalysis data, ARM sounding profiles and AIRS-L2 physical retrievals. But such radiance comparisons clearly disclose the biases in the middle and upper troposphere and avoid any uncertainties associated with level-2 retrievals.

Evaluating global radiation of regional reanalyses over Europe against the satellite-derived SARAH dataset

Author Michael Borsche


Co-authorsA. K. Kaiser-Weiss (Deutscher Wetterdienst), F. Kaspar (Deutscher Wetterdienst)

Within the European Framework Programme 7 project UERRA (Uncertainties in Ensembles of Regional Reanalyses) several regional reanalyses are produced. The grid size resolution of the reanalyses is comparable to the one of the satellite-derived solar radiation estimate SARAH v002 produced by CM SAF (Satellite Application Facility on Climate Monitoring).

In this study we compare solar radiation of all regional reanalyses of that project (from the National Meteorological Services of Sweden (SMHI), Great Britain (UKMO), France (Météo France), and Germany (DWD)) with the satellite estimate on instantaneous to multi-decadal time scales within the period 1982 to 2014. In order to estimate the

synthetic spectra based on the ARM-SGP are used to establish observation uncertainties. MERRA-2 and ERA-interim data at the same 51 occasions are also used generate synthetic AIRS spectra.

For AIRS channels in the CO2 band sensitive to the temperature from surface to 800hPa but not to water vapor, both reanalyses show negative differences from the AIRS observation and such differences are much larger than the observation uncertainties (OU) established above. For channels sensitive to temperature from 400-200hPa, the MERRA-AIRS difference is much smaller than the OC while the ERA-AIRS difference is comparable to the OU.

For channels sensitive to temperature between 800 and 400 hPa, reanalysis and AIRS difference is smaller than or comparable to the OU. The BT differences between both reanalyses and AIRS are negative and significantly larger than the OU for the channels in the H2O band. Such differences cannot be explained by temperature difference alone. The only possible explanation is that both reanalyses have positive biases for the water vapor from 800 to 200 hPa.

Similar positive humidity biases can be seen for the comparisons between reanalyses and AIRS over the 30-40N zone, indicating that it is a systematic bias instead of any coincidence over the ARM site. We further show that such differences in BT are consistent with the differences seen in the comparison of

Evaluate reanalysis with simultaneous in-situ and satellite observations: bracketing the observational uncertainties

Author Xianglei Huang

Affiliation The University of Michigan

Co-authorsXiuhong Chen (Univ. of Michigan), Norman G. Loeb (NASA/Langley), Xiquan Dong (Univ. of Arizona), Baike Xi (Univ. of North Dakota), Erica Dolinar (Univ. of North Dakota), Michael Bosilovich (NASA/GSFC), Seiji Kato (NASA/Langley), Paul Stackhouse (NASA/Langley), William Smith Jr. (NASA/Langley)

Every observation has its own uncertainty. This naturally leads to a question in the evaluation of reanalysis against observations: how good is good enough? Here we answer this question by using two independent observations to bracket observation uncertainties, and then using such uncertainties in the evaluation of MERRA-2 and ERA-interim reanalysis. Using cloud radar observations, we have identified 51 occasions from 2004 to 2013 when AIRS on NASA Aqua flied over the ARM SGP site with no cloud in a 30km-by-30km proximity.

Using the ARM SGP soundings, we then computed synthetic AIRS spectra and compared them with observed AIRS spectra. The brightness temperature (BT) differences between AIRS and the

Section 4


of wind is 1.0-4.5m/s. The temperature observations of three sites show a good consistent against CFSv2, ERA-Interim, except for the 2165m high site Jinchuan, which shows a peak RMSE about 8k at 200hPa level.

The RMSE between temperature observation and MERRA2 is about 4k than those of CFSv2 and ERA-Interim. It is also found that, the observations of the lower altitude sites are relatively more similar than higher sites.

Evaluation of circulation type classifications in five global reanalyses over selected Euro-Atlantic and South-American domains in winter

Author Jan Stryhal

Affiliation Charles University & Academy of Sciences of the Czech Republic

Co-authorRadan Huth (Department of Physical Geography and Geoecology, Faculty of Science, Charles University, Prague, Czech Republic; Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic)

Atmospheric reanalyses have been widely used in synoptic-climatology to study large-scale atmospheric circulation and its links to local weather and climate, including the role that changes in circulation play in trends of climatic

Evaluation of CFSv2, ERA-Interim and MERRA2 datasets with intensive radiosonde data in the lee of the Tibetan plateau

Author Zhiwei HENG

Affiliation Institute of Plateau Meteorology, China Meteorological Administration, Chengdu

The intensive Southwest China vortex observation experiment is conducted in Sichuan province (in the lee of the Tibetan Plateau), from 21 June to 31 July in recent years. This study collects about 1900 high-quality radiosonde data from 4 of the meteorological stations, from 2014 to 2016, to evaluate the quality of the commonly used global datasets ERA-Interim (interim ECMWF Re-Analysis), CFSv2 (NCEP Climate Forecast System Version 2) and MERRA2 (the second Modern-Era Retrospective analysis for Research and Applications) over this steep terrain region.

The stations vary from 520m to 2900m in the altitudes, providing comprehensive observations in the basin and in the highland. The root mean-square errors (RMSE) of relative humidity, meridional wind, zonal wind show general similarity between observations and the three global datasets.

In terms of relative humidity, the RMSE is about 10%-20% below 400hPa, and raises to 30% at higher levels. The RMSE

Evaluating the coherence of reanalyses’ North Atlantic atmospheric circulation using dynamical proxies

Author Davide Faranda

Affiliation CNRS (LSCE CEA-Saclay)

Co-authorsM.C. Alvarez-Castro (LSCE-CNRS CEA Saclay, France), D. Rodriguez (LSCE-CNRS CEA Saclay, France), G. Messori (MISU Stockolm, Sweden), P. Yiou (LSCE-CNRS CEA Saclay, France)

We evaluate the coherence of the dynamical properties of atmospheric circulation over the North Atlantic for several reanalyses datasets (20CR, ERA20CM, CERA20C, NCEP-NCAR).

We measure the instantaneous metrics defined in Faranda et al. (Scientific Reports, 2017), namely the number of degrees of freedom and the persistence of daily averaged sea-level pressure fields. We find that, before 1948, the ensemble means of all reanalyses suffer from a non-physical reduction of the number of degrees of freedom originating from the large spread of the ensemble members.

On the contrary, ensemble members of different datasets show significant shits of the dynamical proxies over time. These shifts are however not coherent among different reanalyses datasets. A comparison with large ensemble of climate models is also presented. The effects of the seasonal cycle are analysed.

been compared to the local water table measurements given by the monitoring network managed by the Regional Agency for Environmental Protection of the Umbria Region (ARPA Umbria Italy). The pointed out good correlation between the trend of soil moisture – the result of precipitation over all meteorological space-time scales – and local water table data of unconfined aquifers authorises further in-depth analyses.

In the line with such promising results, in this paper meteorological observations from ERA-Interim and ERA5 reanalyses are compared with the aim of evaluating: i) the effect of the different models and procedures used to obtain global datasets, and ii) the role played by the characteristics of data on which reanalyses are based (e.g., their temporal and spatial resolution). Attention is focused on the behaviour of water fluxes towards water table as a preliminary phase of the water budget assessment. In fact, reanalyses produce the land surface forecast for soil moisture at four levels (0-7; 7-28; 28-100; and 100-289 cm from the ground level, respectively).

The ultimate goal of this research is to check whether the global datasets – specifically the behaviour of the soil moisture volumetric content – may allow estimating the available groundwater resources at a regional scale.

Section 4


Evaluation of JRA-55C, an Atmospheric Reanalysis Assimilating Conventional Observations Only

Author Chiaki Kobayashi

Affiliation Meteorological Research Institute

Co-authorsH. Endo (Meteorological Research Institute), H. Kamahori (Meteorological Research Institute)

As a subset of the Japanese 55-year Reanalysis (JRA-55) project, the Meteorological Research Institute of the Japan Meteorological Agency conducted a global atmospheric reanalysis that assimilates only conventional surface and upper air observations, with no use of satellite observations, using the same data assimilation system as the JRA-55.

The project, which name is “JRA-55 Conventional (JRA-55C)”, aims to produce a more homogeneous dataset over a long period, unaffected by changes in historical satellite observing systems. In addition, JRA-55AMIP, which is the AGCM experiment, is also conducted. In the experiment, the same model and the same boundary such as the observed SST and sea-ice, greenhouse gases, ozone and aerosols as in the JRA-55 and JRA-55C, are prepared.

ranges, there is a better agreement between the frequency of occurrence of CCMP and measured wind speeds. For wind speed above 10 m/s, occurrence frequency of ERA-I and CCMP winds are much less than that of the measured winds, such that, there is no wind speed above 12.5 m/s from ERA-I and CCMP datasets in the Lavan station.

To investigate the sensitivity of the wave model to the wind field, several wave simulations in the period of 1/10/2009-7/7/2010 were carried out using WAVEWATCH III model forced with ERA-Interm and CCMP wind fields. Application of CCMP wind field compared to ERA-I wind field sometimes results in larger wave height and sometimes vice versa. To evaluate the performance of applied wind fields, the simulated and measured significant wave height (Hs) and peak spectral period (Tp) were compared and error indices were calculated. Results indicated that application of ERA-I and CCMP led to an average underestimation of 30% for Hs and 10% for Tp in both stations.

Evaluation of ERA-Interim and CCMP wind fields for wave simulation in the Persian Gulf

Author Mohammad Hossein Kazeminezhad

Affiliation Iranian National Institute for Oceanography and Atmospheric Science

In this study performance of ERA-Interim (Dee et al., 2011) and CCMP (Atlas et al., 2011) wind fields were evaluated for wave simulation in the Persian Gulf. One of the shortcomings in the Persian Gulf region is the lack of sufficient measured overwater wind data as well as results of atmospheric numerical models which specifically calibrated for this region.

Therefore, it is common that the forcing wind data for wave models are derived from the global wind resources such as ECMWF (European Center for Medium range Weather Forecasting). To do so, wind rose from measurements, ERA-Interim and CCMP wind were compared in Lavan and Siri islands stations located in the northern Persian Gulf in the period of 1/10/2009-7/7/2010.

The measured wind data are collected from synoptic stations located on islands and may affected by the land. Therefore, the recorded wind speeds may be smaller than those occurred overwater. The most frequently occurring wind speed in both stations was in the range of 2.5-5.0 m/s. As can be seen, almost in all wind speed

variables, and to evaluate outputs of climate models. In this kind of research, automated classifications of daily mean sea level pressure or geopotential height patterns represent one of the most prominent approaches.

Such classifications define a few distinguished circulation types (CTs), to which daily patterns are classified according to a similarity measure. So far, no study has aimed at comparing classifications (e.g., CT occurrence frequencies) in multiple reanalyses, and, in general, the effect of reanalysis selection on results has been rather marginalized. The present research focuses on quantifying the differences in CT frequencies in five global reanalyses (ERA-40, NCEP-1, JRA-55, ERA-20C, 20CRv2) during 1961–2000 winters.

We focus on two spatial domains,–Euro-Atlantic and South-American–, each represented by several smaller subdomains covering regions with various climates and numbers of observations assimilated by reanalysis models. Furthermore, for selected subdomains, it will be shown how the choice of the reference reanalysis affects validation of models by ranking 32 CMIP5 GCMs according to their skill to simulate the winter CTs. A total of eight classification methods will be used in parallel to minimize the effect of subjective, unavoidable methodological choices on results.

Section 4


of Meteorology and Climatology MeteoSwiss, Zurich, Switzerland), O. E. Tveito (Norwegian Meteorological Institute, Oslo, Norway) and L. Cantarello (Norwegian Meteorological Institute, Oslo, Norway, Federal Office of Meteorology and Climatology MeteoSwiss, Zurich, Switzerland

Re-analysis aims at providing long-term, high-resolution, dynamically consistent climate datasets useful for environmental applications. Usually, these datasets cover a time period of several decades and they assimilate high-quality and detailed observations into the atmospheric analysis. In UERRA, a FP7 research project of the EU, several regional deterministic and ensemble re-analyses, as well as downscaling procedures based on these re-analyses, are calculated for the past 30-50 years.

With respect to precipitation, regional re-analyses are expected to better represent high threshold events than global re-analysis. The aim of the present study is to evaluate daily precipitation data from the new regional re-analyses of UERRA in two topographically complex sub-regions of Europe, namely the European Alps and Fennoscandia.

Our focus is on aspects of re-analysis uncertainty that may be relevant for hydrological applications, notably the dependence on spatial scale. In comparison with verification of numerical weather predictions, the evaluation of reanalysis data must focus more on assessing the spatial smoothing and

EOS intends to provide a uniform protocol for the evaluation of ocean syntheses, and seek adhesion to this protocol from scientists working on ocean reanalyses worldwide. This work builds-up on previous efforts made within the GODAE and ORA-IP initiatives for intercomparisons. The metrics proposed need to facilitate the assessment of progress in the quality of ocean reanalyses. Detailed metrics are needed also for regional ocean reanalyses and for process-based intercomparisons.

This protocol, still under development, will be presented at the conference in order to foster discussion and obtain feedback from reanalysis experts. The main achievements of the EOS network and a brief presentation of the activities organised in the following months will be also presented.

Evaluation of precipitation in UERRA regional re-analysis datasets for complex terrain regions

Author Cristian Lussana

Affiliation Norwegian Meteorological Institute

Co-authorsF. Isotta (Federal Office of Meteorology and Climatology MeteoSwiss, Zurich, Switzerland), B. Casati (Meteorological Research Division, Environment and Climate Change Canada, Dorval (QC), Canada), C. Frei (Federal Office

Evaluation of Ocean Syntheses: a COST Action to improve our knowledge about ocean syntheses and reanalyses

Author Aida Alvera Azcarate

Affiliation University of Liege

Co-authorsM. Drevillon (Mercator Océan, France), K. Haines (University of Reading, UK), S. Masina (CMCC, Italy), K.A. Peterson (Metoffice, UK), A. Storto (CMCC, Italy)

The COST Action “Evaluation of Ocean Syntheses” (EOS) was initiated in 2014 in order to establish and consolidate a network of European scientists working on the generation and evaluation of ocean syntheses and reanalyses. The main goals of EOS are to improve the coordination of the European efforts in the evaluation of ocean syntheses, to optimize their use and value, to ease their access, to promote their improvement and to raise confidence in their quality.

Through the activities organised by the network, regional intercomparison initiatives of ocean reanalyses have been started (polar regions, Atlantic Ocean). EOS is also co-organising future plans of the Ocean Reanalysis Comparison Project (ORA-IP) for, among other things, establishing a protocol for the next intercomparison exercise, discusssing strategies for the near real-time extension of the current reanalyses and identifying recommendations and good practices for the reanalysis production.

We evaluated JRA-55C by comparing these three datasets, JRA-55, JRA-55C and JRA-55AMIP. The main results are as follows. On the basis of forecast skill, the quality of the JRA-55C is inferior to that of the JRA-55, but the JRA-55C has better temporal homogeneity than the JRA-55. The climatological properties of the JRA-55C are similar to those of the JRA-55 in the troposphere and lower stratosphere, except for high southern latitudes. QBO is properly represented in JRA-55C, which is not appeared in JRA55AMIP.

The pattern correlation of spatial precipitation anomaly of JRA-55C shows temporal homogeneity through the reanalysis period. The radiation balance of JRA-55 and JRA-55C has characteristics similar to those of JRA-55 AMIP (model). Therefore, improvement of the radiation balance of the model is reflected directly in the balance of the reanalysis field.

Section 4


being of direct societal importance. Ocean reanalysis systems are critical for the evaluation of this ocean monitoring indicator as they deliver a 3-D view on the interior of our oceans and its temporal changes from a combined use of ocean observing systems and numerical model techniques.

In this analysis we will present results on the evaluation of global and regional ocean steric sea level under the Ocean State Report activity from a multi-reanalysis approach based on an ensemble product of the Copernicus Marine Service.

In addition, consistency checks through physical budget constraints with the combined use of climate observing systems and reanalyses are performed as they have a large potential to deliver a robust uncertainty assessment and to shed new light on unresolved climate science issues. In particular, complementary information coming from altimetry and gravimetry satellite missions is helpful for qualifying the reanalysis datasets. For this purpose, the sea level budget has been applied, allowing an assessment of the multi-reanalysis approach and the reliability of the ensemble mean.

space–time scales, such as equatorial waves, compared with JRA-25 during the satellite era, and improved the temporal consistency compared with the older reanalyses throughout the reanalysis period, although some issues in JRA-55 were also identified.

Evaluation of steric sea level from the CMEMS ensemble of ocean reanalysis


Affiliation CMCC

Co-authorsKarina von Schuckman (Mercator Océan), Magdalena Balmaseda (ECMWF), Clement Bricaud (Mercator Océan), Charles Desportes (Mercator Océan), Marie Drevillion (Mercator Océan), Yann Drillet (Mercator Océan), Clotilde Dubois (Mercator Océan), Gilles Garric (Mercator Océan), Laura Jackson (UK MetOffice), Matt Martin (UK Met Office), Simona Masina (CMCC), Sandrine Mulet (CLS), Coralie Perruche (Mercator Océan), Isabelle Pujol (CLS), Drew Peterson (UK Met Office), Patricia de Rosnay (ECMWF), Richard Wood (UK Met Office), Hao Zuo (ECMWF)

Thermal expansion of seawater is a major driver of global mean sea level change. Quantifying the effect of the seawater density changes on sea level variability is of crucial importance for climate change studies, as the cumulative sea level rise can be regarded as an important climate change indicator, as well as

uncertainties, the magnitude of which may be significant at the resolution of modern re-analyses and, hence, could affect a scale-dependent evaluation. This difficulty is addressed in the Alpine section of our analysis by introducing a new probabilistic rain-gauge dataset which explicitly quantifies uncertainties by ensembles.

Evaluation of representation of atmospheric circulation and climate variability in the JRA-55 reanalysis

Author Yayoi Harada

Affiliation Meteorological Research Institute/Japan meteorological Agency

This study investigates the quality of the Japanese 55-year Reanalysis (JRA-55, Kobayashi et al. 2015), which is the second global reanalysis constructed by the Japan Meteorological Agency (JMA), comparing with other reanalyses and observational datasets. Improvements were found in the representation of atmospheric circulation on the isentropic surface and in the consistency of momentum budget based on the mass-weighted isentropic zonal mean (MIM) method.

The representation of climate variability in several regions was also examined. The results indicate that JRA-55 generally improved the representation of phenomena on a wide range of

filtering properties of the atmospheric model considered, while the forecast error is less relevant because it is expected to be rather small due to the frequent data assimilation cycles.

The evaluation is based on a comparison against conventional climatological datasets derived from spatial analyses of high-resolution rain-gauge networks. The Alpine rain-gauge dataset covers territories of seven countries and encompasses more than 5300 daily rain-gauge observations on average. In Fennoscandia, we focus on Norway, Sweden and Finland where a dataset of approximately 2000 daily rain-gauge observations is available.

Our evaluation strategy combines “standard” verification measures of systematic errors (such as the bias and root mean squared deviations) with spatial verification methods, which account for the presence of features and for the coherent spatial structure inherent in precipitation fields, and provide enhanced diagnostics (e.g. scale-separation approaches inform on the scale-structure and scale-dependence of the error).

Scale dependence of the uncertainty/accuracy is examined in our analyses by considering (nested) hydrological catchments of variable size and by decomposing precipitation fields into (orthogonal) wavelets of variable scale. A difficulty for an unbiased evaluation of re-analyses is that reference datasets themselves are subject to

Section 4


Evaluation of water cycle components in the Upper Blue Nile basin based on an ensemble of water resources reanalysis products.

Author Marika Koukoula

Affiliation University of Connecticut

Co-authorsEfthymios I. Nikolopoulos, Zoi Dokou, Semu Moges, Amvrossios C. Bagtzoglou, (University of Emmanouil), N. Anagnostou (Department of Civil and Environmental Engineering, University of Connecticut)

Availability of multiple global water resources reanalysis (WRR) products has provided a unique opportunity to advance understanding of terrestrial hydrologic processes at regions where in situ information is sparse or nonexistent. Africa is a continent where this aspect is particularly emphasized because it is generally characterized by sparse hydrologic observations while at the same time there is need for efficiently managing water resources to enhance food and water security in the area. Managing water resources in a sustainable manner requires at the very least an adequate characterisation of hydrological fluxes (precipitation, streamflow, evapotranspiration, groundwater) and states (soil moisture) at monthly, seasonal and annual scale. In this work we present a comprehensive evaluation of water cycle components

assimilated. While this change in data streams does lead to a discontinuity in the assimilated ozone fields in MERRA-2, making it not useful for studies in decadal (secular) trends in ozone, this choice was made to prioritize demonstrating the value NASA’s high-quality research data in the reanalysis context.

The MERRA-2 ozone is compared with independent satellite and ozonesonde data, focusing on the representation of the spatial and temporal variability of stratospheric and upper-tropospheric ozone. The comparisons show agreement within 10% (standard deviation of the difference) between MERRA-2 profiles and independent satellite data in most of the stratosphere. The agreement improves after 2004, when EOS Aura data are assimilated. The standard deviation of the differences between the lower-stratospheric and upper-tropospheric MERRA-2 ozone and ozonesondes is 11.2% and 24.5%, respectively, with correlations of 0.8 and above. This is indicative of a realistic representation of the UTLS ozone variability in MERRA-2. After 2004, the upper tropospheric ozone in MERRA-2 shows a low bias compared to the sondes, but the covariance with independent observations is improved compared to earlier years. Case studies demonstrate the integrity of MERRA-2 analyses in representing important features such as tropopause folds.

For comparison purposes, we perform the analyses on the 56 members and the ensemble mean of the 20CRv2c reanalysis, as well as for another reanalyses products, ERA-20C and NCEP, in order to properly estimate and discuss the uncertainties and be capable to assess the ability of reanalyses to reproduce the mechanisms that lead to European temperature extremes.

Evaluation of the Ozone Fields in NASA’s MERRA-2 Reanalysis

Author Steven Pawson

Affiliation NASA GSFC

Co-authorsK. Wargan (NASA GSFC), G. Labow (NASA GSFC), S Frith (NASA GSFC), N. Livesey (NASA JPL), G. Partyka (NASA GSFC)

The assimilated ozone product from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), produced at NASA’s Global Modeling and Assimilation Office (GMAO) is summarized. The reanalysis begins in 1980 with the use of retrieved partial-column ozone concentrations from a series of Solar Backscatter Ultraviolet Radiometer (SBUV) instruments on NASA and NOAA spacecraft.

Beginning in October 2004, retrieved ozone profiles from the Microwave Limb Sounder (MLS) and total column ozone from the Ozone Monitoring Instrument (OMI) on NASA’s EOS Aura satellite are

Evaluation of the ensemble reanalysis ability to reproduce mechanisms leading European temperature extremes

Author M. Carmen Alvarez-Castro

Affiliation Laboratoire des Sciences du Climat et de l’Environnement (LSCE/IPSL/CEA-CNRS)

Co-authorsD. Faranda, P. Yiou. (LSCE/IPSL, France)

The atmospheric circulation is an important driver of temperature variability. Weather regimes are typical atmospheric circulation patterns obtained using a cluster analysis. Climate decadal variability can induce changes in those frequencies. We investigate how the atmospheric circulation might have evolved in the past century, focusing specifically on the weather regimes associated with temperature extremes in Western-Europe.

The 20CR is the longest reanalysis available that assimilates only surface pressure observations since 1851 using an Ensemble Kalman Filter data assimilation method, producing an ensemble of 56 members of reanalysis fields. Therefore, the differences among the 56 members provide an estimate of the uncertainty for the reanalysis.

Section 4


thus, an evaluation of these products is strongly needed before to use them in applications.

Classical validation of satellite and reanalysis products still relies on the use ground networks of rain gauges hence the problem of investigating the satellite and reanalysis performances in data-scarce regions in not eliminated. Given three collocated datasets (a triplet) of precipitation, Triple Collocation (TC) offers a valid alternative to characterize rainfall product errors without relying on ground-based observations, but TC is subject to several assumptions such as the existence of an uncorrelated error between the products of the triplet – a requirement that is hardly satisfied within global non-gauge based precipitation estimates.

Recently, Brocca et al. (2014) developed a method for estimating rainfall from satellite soil moisture observations based on the principle that the soil can be treated as a “natural raingauge”. In contrast with classical satellite precipitation products, this new bottom-up approach attempts to measure rainfall by calculating the difference between two successive SM measurements derived from a satellite sensor.

Global evaluation of ERA-Interim and other global rainfall estimates over land without ground-based observations by using Triple Collocation Analysis

Author Christian Massari

Affiliation IRPI- CNR

Co-authorsWade Crow (USDA – Hydrology and Remote Sensing Laboratory, Beltsville, Maryland), Luca Brocca (IRPI-CNR, Perugia, Italy)

Precipitation is a fundamental physical process of the global hydrological cycle, and its temporal and spatial distribution has a significant impact on many land applications. Acquiring accurate and real-time precipitation data is essential to researching the global hydrological cycle, mitigating worldwide drought and flooding, simulating land surface hydrological processes, and understanding global climate change.

Despite this importance, ground-based estimates of rainfall over land are scarce within Africa, Central Asia and South America hence, relying on these estimates for studying processes at large scales is often impossible. Satellite and reanalysis rainfall products offer a valid alternative to ground based observations but are subjected to some limitations that depend on the type of precipitation, topography and type of the background surface (Ebert et al. 2007)

Front statistics in modern reanalyses using an automated front recognition over East Asia

Author Eunho Choi

Affiliation Seoul National University

Co-authorsG.H. Lim (Seoul National University)

A front is one of most important part of weather and climate over East Asia, bringing severe weather events such as heavy rain, damaging winds. We have tried to recognize a front given horizontally gridded variables on a specific pressure level through an automated computer algorithm. Then, we have applied our approach to state-of-the-art reanalyses; ERA-Interim, CFS, and MERRA. We have analyzed the result from front recognition to get statistics of front frequencies and front intensities (defined by precipitation rate, upward wind, horizontal temperature gradient, convective instability and so on) and compared it across the reanalyses. We will try to elaborate possible explanation to a reason why the differences among the reanalyses exist.

for the Upper Blue Nile basin in Ethiopia estimated from four state-of-the-art WRR products.

Specifically, evaluation is carried out for two datasets produced through NASA’s Land Data Assimilation System (LDAS) at global (GLDAS v2) and regional (FLDAS) scale and two versions (tier 1&2) of the global WRR product of the EU Earth2observe project. Each product includes a multi-model ensemble output. The final ensemble output, considering all products, incorporates differences in forcing, model space/time resolutions and assimilation procedures used in each WRR product.

Thus, evaluation of the ensemble output with respect to available long-term hydrologic observations for rainfall, streamflow and groundwater levels allows us to assess the accuracy of current WRR products and the range of associated uncertainty due to differences in forcing and model structure. Bias and uncertainty characteristics are presented as function of hydrologic variables and temporal scale (monthly, seasonal and annual). Results from this analysis highlight the current strengths and limitations of available WRR datasets for analyzing the hydrological cycle and dynamics of East Africa region and provide unprecedented information for both developers and end users in similar hydroclimatic regimes.

Section 4


for Medium-Range Weather Forecasts’ (ECMWF) ERA-Interim reanalysis, 2) the Monitoring Atmospheric Composition and Climate (MACC) reanalysis and 3) NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis. The ERA-Interim cyclone tracks are used here to establish the long-term relationship between cyclones and ozone observations (since 1988).

The MACC reanalysis data set, which covers the period 2003–2012, is produced with the ECMWF integrated forecast system (IFS) model two-way coupled to a chemistry transport model (CTM). Since the MACC reanalysis uses a similar atmospheric model to ERA-Interim, MACC is used to explore the mechanisms within case study cyclones that can influence surface ozone concentrations at Mace Head and Monte Velho.

The MERRA-2 reanalysis also provides 3D distributions of ozone, although less ideal for analysis of surface ozone concentrations since MERRA-2 ozone under represents ozone variability in the lower troposphere as MERRA-2 has a less detailed chemistry and emissions scheme for the troposphere compared to the MACC reanalysis.

However, the MERRA-2 reanalysis has the potential to identify more features within the cyclones as the resolution is higher than the MACC reanalysis, and

and wavelet coherence. The period considered was 1905-2005. We found a good agreement among all indices and a see-saw pattern adequately captured by both reanalyses after 1957. Before 1957, a weaker see-saw pattern was reflected at both reanalyses, slight better represented with 20CR. The results provide valuable information for climate studies linked to middle and high latitudes of the Southern Hemisphere.

Influence of mid-latitude cyclones on European background surface ozone investigated in observations and multiple reanalyses

Author Katherine Emma Knowland

Affiliation Universities Space Research Association (USRA) / GESTAR & NASA GMAO

Co-authorsR.M. Doherty (School of Geosciences, University of Edinburgh, Edinburgh, UK), K.I. Hodges (Department of Meteorology, University of Reading, Reading, UK), L.E. Ott (NASA/GMAO)

The relationship between springtime mid-latitude cyclones and background ozone at two rural monitoring sites on the west coast of Europe – Mace Head, Ireland and Monte Velho, Portugal – is explored using a combination of observations and three reanalyses: 1) the European Centre

index has been derived from different reanalysis, but it was affected by bias of pressure values at high southern latitudes. Due to these reasons, SAM index derived by Marshall (based on appropriately located station observations) is considered in many climate studies, but it is only available since 1957. In order to understand how decadal to interdecadal hemispheric and regional processes have evolved over time, long time climate indices are needed, but the limitations originated by the lack of data in the first part of 20th Century must be taken into account. 20th Century Reanalysis (NOAA-CIRES) and ERA-20C (ECMWF) provide datasets spanning the entire twentieth century.

In this work, these datasets were considered in order to construct “Historical” SAM indices using sea level pressure (SLP) values of 20CR (SAM20) and ERA-20C (SAMERA20) according to Gong and Wang definition (normalized differences of SLP between 45°S and 60°S). Likewise, other indices were constructed, only considering the grid points in the vicinity of the surface stations used by Marshall (SAM20M and SAMERA20M respectively) with the aim to perform a comparison with the observational index.

A SAM index derived with other methodology (EOF) was also taken into account (AAO20). All these indices were analyzed and compared on a range of timescales by spatial patterns analysis, correlation analysis, wavelet transform

Historical Southern Annular Mode index derived from 20th Century reanalysis and ERA-20C: an overview

Author Mariana Barrucand

Affiliation Conicet/University of Buenos Aires

Co-authorsM. E. Zitto (Facultad de Ingeniería, Universidad de Buenos Aires, Buenos Aires, Argentina), R. Piotrkowski (Facultad de Ingeniería, Universidad de Buenos Aires, Buenos Aires, Argentina. Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, San Martín, Prov. de Buenos Aires, Argentina), P. Canziani (Unidad de Investigación y Desarrollo de las Ingenierías, Facultad Regional Buenos Aires, Universidad Tecnológica Nacional, Consejo Nacional de Investigaciones Científicas y Técnicas CONICET, Buenos Aires, Argentina)

With the aim of understanding climate processes while managing large datasets and model outputs for climate variability and change studies, it is often convenient to define climate indices. These are based on physical principles and statistical methods and they can be derived from observations or from reanalysis products.

One climate index of special interest at Southern Hemisphere is the Southern Annular Mode (SAM), the principal mode of variability of the atmospheric circulation in the SH extratropics. This

Section 4


Satellite based products perform reasonably well within tropical forests and Eastern Asia and North America but are subjected to errors at northern latitudes. SM2RAINasc performs better in the Southern Hemisphere in areas where neither ERA-Interim nor the satellite-based datasets provide good results.

IIntercomparison of regional and global oceanic reanalyses in the Mediterranean Sea

Author Jonathan Beuvier


Co-authorsM. Hamon (Mercator Océan), C. Desportes (Mercator Océan), M. Drévillon (Mercator Océan), J.-M. Lellouche (Mercator Océan), Y. Drillet (Mercator Océan)

One of the objectives of the COST action “Evaluation of Ocean Syntheses” (see presentation by Alvera-Azcárate et al.) is to foster regional ocean reanalyses intercomparisons, which focus on the evaluation of specific regional processes and variability, in particular in ocean and climate variability “choke points” such as the Mediterranean Sea. An intercomparison in the Mediterranean Sea, also considering global ocean reanalyses, will take place in 2017-2018.

In this context, we show preliminary results of the evaluation of the functioning of the Mediterranean Sea

consistence of annual variability and dispersion in the lower troposphere between REA and ADJ, and the dispersion of REA were obviously higher than ADJ in the middle and upper troposphere.

The linear trends of specific humidity are consistent between REA and ADJ with wetting trends in the lower troposphere while different in the middle troposphere with wetting trends from ADJ and drying trends from REA. The linear trends of relative humidity in the troposphere were obviously different between REA and ADJ with drying trends from REA while wetting trends and more significant wetting in the middle and upper troposphere. The spatial distribution of trends from ADJ at 118 stations and REA at the corresponding grids showed remarkable difference over China.

In this contest, SM2RAIN offers an additional non-gauge based dataset for properly applying TC on a global scale In this study, TC analysis has been applied to the rainfall estimates derived from 1) ERA-Interim, 2) SM2RAIN via inversion of Advanced SCATterometer (ASCAT), SM2RAINasc, 3) the NOAA Climate Prediction Center morphing (CMORPH) and 4) the TRMM Multi-satellite Precipitation Analysis (TMPA 3B42RT) in the period 2007-2012. We found that that ERA-Interim dataset performs relatively well in the Northern Hemisphere while have some limitations in Africa and South America.

and relative humidity over China between radiosonde and the third generation reanalysis was undertaken.

The relative difference, correlation, standard deviation and linear trend during 1979–2015 derived by RAW, ADJ and REA were analyzed.

The results revealed significant discontinuities in the raw radiosonde specific humidity and relative humidity time series in China and the homogenization of original data is essential for reanalysis assessment. Homogenization adjusted the RAW with a substantial correction before 2000s. The average specific humidity and relative humidity over China from REA were generally wetter than those from radiosonde and the differences of relative humidity were higher than specific humidity.

Meanwhile the differences in the upper troposphere were larger than those in the lower troposphere, and the differences between REA and ADJ were more remarkable than the difference between REA and RAW. The differences in spring and autumn were more significant than those in summer. The consistency of specific humidity and relative humidity from four reanalysis is high and JRA-55 were relative similar with radiosonde with dryer humidity than other three reanalysis.

The correlation and standard deviation ratio of specific humidity and relative humidity demonstrated the higher

therefore is used in conjunction with the MACC reanalysis to provide a measure of uncertainty to the case study analysis.

We found the main source of high ozone to these two sites is from the stratosphere, which is well represented in both the MERRA-2 reanalysis and the MACC reanalysis, and occurs either from direct injection into the cyclone or associated with aged airstreams from decaying cyclones that becomes entrained and descends towards the surface within new cyclones over the region.

Inter-comparison of upper air water vapor over China between Radiosonde and the third generation Reanalysis Datasets

Author Zhang Siqi

Affiliation National Climate Center

Co-authorsGuo Yanjun (National Climate Center, Beijing 100081, China), Wang Guofu (National Climate Center, Beijing 100081, China)

Based on quality controlled (RAW) and homogenized (ADJ) radiosonde data from 118 stations in China and monthly mean specific humidity and relative humidity from four reanalysis datasets (REA) which included ERA-Interim, JRA55, MERRA and CFSR, a preliminary comparison of upper air specific humidity

Section 4


Interdecadal variation of atmospheric overturning circulation in the ERA-20C reanalysis

Author Bo Dong

Affiliation University of Reading

The phase transition of the Interdecadal Pacific Oscillation (IPO) is one possible cause of the early 2000 global warming hiatus. To physically understand the modulation, changes in atmospheric overturning circulations and the associated energy transport for the IPO and global warming (GW) are quantified and contrasted using the ERA-20C reanalysis data.

Multiple linear regression analyses show that both warm IPO and GW modes feature significant weakening and eastward shift of the Pacific Walker circulation, and strengthening of the Hadley circulation, characterized by southward shift of the ITCZ and intensified deep tropical convection with contracted meridional extent. Also, strengthening in the subtropical jet, increases in tropospheric temperature and humidity are found.

The resemblance of the two trend modes indicates that circulation anomalies of warm (cold) IPO phases amplify (dampen) the anthropogenic warming-induced circulation trends. Besides, a few implausible circulation trend patterns are found in the GW mode, such as

Homogenization removed system error caused by radiosonde instrument change and updates to the radiation adjustment method and observation system of RAW. Hence, the correlation between REA and ADJ was higher than that between REA and RAW. The mean difference between REA and ADJ was approximately 1°C during 1981–2010, while REA was mostly cooler than ADJ in the troposphere and warmer in the stratosphere. Significant correlation demonstrated the consistency between the annual variability of REA and ADJ.

The linear trends were consistent between REA and ADJ, with warming in the lower and middle troposphere and cooling in the middle stratosphere. Greater uncertainty was apparent for the upper troposphere and lower stratosphere. ERA-Interim, JRA55 and MERRA were generally closer to homogenized radiosonde temperatures than the other reanalysis datasets.

Intercomparison of Upper Air Temperature over China between Radiosonde and Multiple Reanalysis Datasets

Author Yanjun Guo

Affiliation National Climate Center/China Meteorogical Administration

Co-authorsSiqi Zhang (NCC, CMA), Jinghui Yan (NCC, CMA), Zhe Chen (National Meteorological Information Center NMIC, CMA), Xin Ruan (NMIC, CMA)

Based on quality controlled (RAW) and homogenized (ADJ) radiosonde temperatures at 10 pressure levels from 118 stations across China, and monthly mean temperatures from 8 reanalysis datasets (REA) including NCEP-1, NCEP-2, ERA-40, ERA-Interim, JRA-55, 20CR, MERRA and CFSR, a preliminary comparison of upper air temperature over China between radiosonde and reanalysis data was undertaken.

The mean difference, correlation, standard deviation and linear trend of upper air temperature based on original and homogenized radiosonde and reanalysis temperature during 1981–2010 were analyzed. Generally, homogenized temperatures averaged over China were cooler than RAW, and the negative adjustment in the upper troposphere and lower stratosphere was more significant than in other layers.

(water masses properties, transports through the Strait of Gibraltar, oceanic deep convection) for both global (GLORYS, Ferry et al. 2012) and regional (MEDRYS, Hamon et al. 2016) reanalyses. Global products have a too high water transports through the Strait of Gibraltar (both in free runs and in assimilated runs), leading to a negative net salt transport for the Mediterranean Sea in long-term average (opposite to what is observed), and also to an important decrease of the salinity of the surface layer (0-150m). The intermediate layer (150-600m) is too high and too fresh in the free runs. Moreover, the deep layers (below 600m) display an unrealistic interannual variability, both in temperature and salinity, before year 2005 and the substantial deployment of the Argo network in the Mediterranean. For the deep convection, a focus is made on winter 2013 in the Gulf of Lion, to benefit from the oceanic Special Observation Period of the HyMeX program (Estournel et al. 2016).

Section 4


Multidecadal Rainfall Variability in Sahel

Author Ellen Berntell

Affiliation Department of Meteorology, Stockholm University

The Sahel is a water vulnerable region which exhibits strong inter-annual rainfall variability. During the 20th century the Sahel region experienced extended dry periods and droughts, with devastating effects on the livelihoods of the people in the region. In this study the multidecadal variability of Sahel precipitation is examined in the gridded observational dataset CRU and in the 20th-century reanalysis ERA20C.

Additionally, we use the Hadley sea surface temperature and sea level pressure datasets and the coupled reanalysis CERA20C. Our analysis of the Sahel (10−18N, 20W -30E) July-September rainfall using CRU shows a clear multidecadal variability with a dominating period of 60-80 years and a high correlation to the North Atlantic sea surface temperatures on a multidecadal scale.

Using a global field correlation and a single value decomposition we could see that the highest correlation between low-pass filtered Sahel rainfall and sea surface temperatures was located in the mid-latitudes and in the sub-polar region as well as in eastern North

These OMIs have been operationally implemented starting from the physical reanalysis products and then they have been applied to the operational analyses. Sea surface temperature, salinity, height as well as heat, water and momentum fluxes at the air-sea interface have been operationally implemented since the reanalysis system development as a real time monitoring of the data production.

Their consistency analysis against available observational products or budget values recognized in literature guarantees the high quality of the numerical dataset. The results of the reanalysis validation procedures are yearly published in the QUality Information Document since 2014 available through the CMEMS catalogue (http://marine.copernicus.eu), together with the yearly dataset extension.

New OMIs of the winter mixed layer depth and the heat content will be presented, in particular we will analyze their time evolution and trends starting from 1987. Consistency analysis between OMIs computed from global, regional reanalysis and analyses datasets will be shown as well. At the end, the focus will be on 2016 sea state and circulation of the Mediterranean Sea and its anomaly with respect to the climatological fields to detect the 2016 peculiarities.

Monitoring and long-term assessment of the Mediterranean Sea physical state

Author Simona Simoncelli

Affiliation Istituto Nazionale di Geofisica e Vulcanologia

Co-authorsClaudia Fratianni (INGV), Emanuela Clementi (INGV), Massimiliano Drudi (INGV), Jenny Pistoia (INGV), Alessandro Grandi (INGV), Damiano Del Rosso (INGV), Andrea Storto (CMCC)

The near real time monitoring and long-term assessment of the physical state of the ocean are crucial for the wide CMEMS user community providing a continuous and up to date overview of key indicators computed from operational analysis and reanalysis datasets.

This constitutes an operational warning system for the advanced prediction of extreme events, stimulating the research towards a deeper understanding of them and consequently increasing CMEMS products uptake. Ocean Monitoring Indicators (OMIs) of some Essential Ocean Variables have been identified and developed by the Mediterranean Monitoring and Forecasting Centre (MED-MFC) under the umbrella of the CMEMS MYPWG (Multy Year Products Working Group).

strong increases in the tropospheric temperature over the Antarctic, and decreases in atmospheric humidity in the northern extratropics. The causes of these spurious changes in the ERA-20C reanalysis deserve further investigation.

Long-term trends in the stratosphere using reanalyses

Author Michal Kozubek

Affiliation Institute of Atmospheric Physic

The long-term trend of different atmospheric parameters has been studied separately during previous years in many papers. This study is focused on the temperature, wind (u and v component), geopotential height and watervapour trends during 1979-2016. We present the trend for each month with respect to ozone turnaround during mid 1990s.

The different reanalyses (MERRA, ERA-Interim, JRA-55 and NCEP-NOE) are used for comparison. We analyzed every grid point to reduce the problem with zonal averages indifferent pressure levels. The results will show the complex view on the trend in the middle atmosphere (troposphere, stratosphere and lower mesosphere).

This comparison can give us the clue which reanalysis is better for studying different phenomena (QBO, NAO, ENSO, etc.) and which one has some issues.

Section 4


correcting the mean state causes the deceleration of the warming trend and alters the long-term climate signal. The ensemble spread reflects the long-lasting memory of the initial conditions and the convergence of the system to a solution compatible with surface fluxes, ocean model and observational constraint.

Observations constrain the ocean heat uptake trend of the last decades of the 20th century, which is similar to estimations from the post-satellite era. An ocean heat budget analysis attributes ORA-20C heat content changes to surface fluxes in the first part of the century. The heat flux variability reflects spurious signals stemming from ERA-20C surface fields, which in return result from changes in the atmospheric observing system.

The influence of the temperature assimilation increments on the heat budget is growing with time. Increments control the most recent ocean heat uptake signals, highlighting imbalances in forced reanalysis systems as well in the ocean as in the atmosphere.

understanding of the climate as they confront observations with model in a consistent and systematic way.

This presentation will describe assessment results of CERA-20C such as trends of the analysis field and quality of the observations.

Ocean heat content variability in an ensemble of 20th century ocean reanalyses

Author Eric de Boisseson

Affiliation ECMWF

Co-authorsM. Balmaeda (ECMWF) and M. Mayer (University of Vienna/ECMWF)

In the context of the EU-funded ERA-CLIM2 project, ECMWF produced a ten-member ensemble of 20th century Ocean ReAnalyses called ORA-20C. ORA-20C assimilates temperature and salinity profiles and is forced by the ECMWF 20th century atmospheric reanalysis (ERA-20C) over the 1900-2010 period. This study attempts to identify robust signals of ocean heat content change in ORA-20C and detect contamination by model errors, initial condition uncertainty, surface fluxes and observing system changes.

It is shown that ORA-20C trends and variability in the first part of the century result from the surface fluxes and model drift towards warmer mean state and weak meridional overturning circulation. The impact of the observing system in

Observation feedback information of the ECMWF coupled climate reanalysis

Author Yuki Kosaka

Affiliation JMA/ECMWF

Co-authorsPatrick Laloyaux (ECMWF), Eric de Boisseson (ECMWF), Per Dahlgren (ECMWF), Dinand Schepers (ECMWF)

The European Centre for Medium-Range Weather Forecasts (ECMWF) has developed a coupled assimilation system that ingests simultaneously ocean and atmospheric observations in a coupled ocean-atmospheric model. This approach has been used to produce a new coupled 20th-century reanalysis, called CERA-20C, which provides a long record of low-frequency climate variability using a consistent set of observations.

To account for errors in the observational record as well as model error, CERA-20C provides a 10-member ensemble of reanalyses. Regarding observation data, surface pressure and marine wind observations as well as ocean temperature and salinity profiles are assimilated in the CERA-20C assimilation system.

These observation data, as well as model departures before and after assimilation and usage flags, are stored in observation feedback archive files. These files can be used to improve our

Atlantic with values around R = 0.8. Similarly, ERA20C reanalysis dataset exhibits multidecadal rainfall variability in Sahel with a dominating period of 60-80 years, however largely out of phase with the observational dataset and with no correlation to the North Atlantic sea surface temperatures.

The composite analysis of low-pass filtered data showed a clear increase of rainfall across Sahel in wet compared to dry years for both the CRU observational and ERA20C reanalysis datasets. The composite difference for the sea level pressure and surface temperature suggest that a strengthening of the thermally driven meridional pressure gradient between Sahara and the Coast of Guinea in wet compared to dry years is the driving mechanism for the multidecadal rainfall variability in Sahel for both the observational and reanalysis dataset.

The strengthened gradients both increase the moisture in the region through increased moisture flux and intensifies the monsoon system through strengthened monsoon winds, resulting in increased rainfall. The study shows that it is challenging to capture the multidecadal Sahel rainfall variability in reanalysis data. Reasons for this behavior are discussed and the behaviour of the Sahel precipitation is also analyzed for CERA20C.

Section 4


Planetary boundary layer depicted by most recent regional reanalyses

Author Ronny Petrik

Affiliation Helmholtz Centre Geesthacht Institute for Coastal Research

Co-authorsBeate Geyer (Helmholtz-Zentrum Geesthacht, Institute for Coastal Research), Burkhardt Rockel (Helmholtz-Zentrum Geesthacht, Institute for Coastal Research)

“Within the framework of the project openFRED feed in power within complex electricity grids are simulated with energy system models over a couple of years. The energy system models require to have input data for the energy production of each single renewable power plant. One of the possibilities is to rely on the data from regional hindcasts, because they allow to get a detailed picture of the atmospheric processes during the last decades. This details can still not be provided by the global reanalysis products as ERA, NCEP or MERRA. However, the main question arises how suitable are the regional hindcasts for the application with energy system modelling.

Our main focus is on the simulation of feedin power with respect to solar plants, wind turbines and hydroelectric power stations. As a first step, we aim at investigating the performance

The radiosonde and marine weather observations captured detailed time variations and vertical structures of temperature, wind and humidity associated with the Beaufort High, synoptic-scale cyclone, polar low and seasonal change.

While 4 atmospheric reanalyses (ERA-Interim, CFSv2, MERRA, JRA-25) and initial values of the forecast from 8 weather centers around the world from the TIGGE (THORPEX Interactive Grand Global Ensemble), roughly reproduced the above characteristics, there were some differences.

Compared to the observation, the large differences were seen in the temperature near the boundary layer and tropopause, wind speed in the whole troposphere and water vapor in the lower troposphere.

The spread among the datasets were also large for those variables. It is likely that the discrepancies are due to different treatments of snow/ice processes and of vertical resolution among the models using for the datasets.

positive polarity, indicative of antarctic ozone depletion and Green House Gases induced warming of sea surface temperatures. All these kinematic properties of circulation elements observed in the reanalyses are used as a benchmark to evaluate the CMIP5 models’ performance in reproducing them. Evaluating the performance of the historical runs of the CMIP5 models allows for models’ selection and provides a baseline for analysing their projections.

Performance of objective analysis data over the Pacific Arctic Ocean in summer based on meteorological observations during the R/V “Mirai” Arctic cruises

Author Kazuhiro Oshima

Affiliation Japan Agency for Marine-Earth Science and Technology

Co-authorsM. E. Hori (JAMSTEC), Y. Kawai (JAMSTEC), K. Sato (NIPR), J. Inoue (NIPR)

We evaluated the performance of objective analysis datasets over the Pacific Arctic Ocean, the Chukuchi and Bering Seas based on meteorological observations during the R/V Mirai Arctic cruises in the summer of 2013, 2014 and 2015.

Performance evaluation of CMIP5‘s characterisation of circulation over Southern Africa and its adjacent oceans using reanalyses.

Author Teboho Nchaba

Affiliation University of Cape Town

Co-authorsC Lennard (Climate System Analysis Group, University of Cape Town),

The third generation reanalyses, the CFSR, MERRA-2, and ERA-Interim, are used in this study to evaluate the performance of the Coupled Model Intercomparison Project Phase 5 (CMIP5) historical runs in characterizing atmospheric circulation over Southern Africa and its adjacent oceans. The evaluation is performed for austral summers during the satellite era between 1980 and 2004. Reanalyses show decreases in near surface wind speeds, at 850 hPa and 10-m above ground level, over the South East Atlantic and west coast of Southern Africa over the study period.

These changes in speeds are associated with changes in the intensity of and a poleward migration of the South Atlantic Anticyclone, the midlatitude westerlies, the storm tracks and the descending limb of the Hardly Cell.

The Southern Annular Mode indices extracted from the reanalyses also show an inclination towards their

Section 4


The ARCGATE estimates (currently available October 2004 to May 2010) are derived from mooring data in the four straits under the constraint of mass-, and salinity conservation and include realistic assumptions about freshwater input. We compare these new and largely independent flux estimates (i.e. most ARCGATE observations have not been assimilated in the reanalysis) to data of the Centro Euro-Mediterraneo sui Cambiamenti Climatici Global Ocean Reanalysis System “C-GLORS, Version 5” and the latest ECMWF Ocean Reanalysis System “ORAS5”. We investigate the differences between the datasets by preparing Hovmoeller plots of volume-, temperature- and freshwater transports.

Generally, the patterns agree qualitatively at most locations. An exception are discrepancies in Davis Strait transports at the West Greenland slope region, where upper-ocean volume transports are northward in ARCGATE throughout the year whereas they are northward only during the spring season in C-GLORS and during the spring and summer season in ORAS5.

Comparing time series of total volume-, temperature- and freshwater transports through each strait from ARCGATE against the C-GLORS and ORAS5 data we find good quantitative agreement for both reanalyses only in Fram Strait volume-, and in Bering Strait temperature transports.

Reanalysis-based volume-, temperature- and freshwater transports through arctic gateways vs. mooring-derived estimates

Author Sebastian Stichelberger


Co-authorsM. Pietschnig (University of Vienna, Department of Meteorology and Geophysics, Vienna, Austria), M. Mayer (University of Vienna, Department of Meteorology and Geophysics, Vienna, Austria), T. Tsubouchi (Alfred Wegener Institute, Climate Sciences – Physical Oceanography of the Polar Seas, Bremerhaven, Germany), A. Storto (Centro Euro-Mediterraneo sui Cambiamenti Climatici, Ocean Modeling and Data Assimilation Division, Bologna, Italy), H. Zuo (ECMWF, Reading, United Kingdom), L. Haimberger (University of Vienna, Department of Meteorology and Geophysics, Vienna, Austria)

Recently, new estimates of volume-, temperature and freshwater transports into the Arctic Ocean through the four major gateways (Davis-, Fram-, and Bering Strait and the Barents Sea Opening) have become available through the ARCGATE project (“Maximizing the potential of the Arctic Ocean Gateway array”).

Precipitation over monsoon Asia: a comparison of reanalyses and observations

Author Andrea Toreti

Affiliation European Commission, Joint Research Centre

Co-authorsA. Ceglar (European Commission Joint Research Centre), G. Balsamo (European Centre for Medium-Range Weather Forecasts), S. Kobayashi (Japan Meteorological Agency)

Reanalyses represent an essential source of information for impact modelling and monitoring in areas of the world characterised by sparse observational network and/or limited data access. This study focuses on Monsoon Asia, a key agricultural region of the world.

Four reanalyses (ERA-Interim, ERA-Interim Land, AgMerra and JRA-55) are analysed and compared with two gridded observational datasets: Aphrodite and Chirps. Seasonality, extremes and distributional differences are assessed by using a combination of recently proposed statistical methods. The main results show the good performance of the bias-corrected reanalysis AgMerra, the temporal homogeneity of JRA-55 and the good spatial representation provided by ERA-Interim Land.

of various hindcasts with respect to the representation of the planetary boundary layer (PBL), i.e. how well the thermo- and hydrodynamic state of the PBL is captured by the models. Our study involves, on the one side, regional hindcasts utilizing state-of-the-art/superb data assimilation to force the model to observations. Thanks to the UERRA project most recently reanalyses were performed over Europe and provided by various European meteorological services (for instance the COSMO-REA6 product by the DWD). On the other side, our study involves regional hindcasts based on downscaling global reanalyses (as done for example at the Helmholz-Zentrum in Geesthacht).In the presentation we address the problem of finding evaluation data independent in the sense of a data assimilation process. The evaluation of the daily cycle of the PBL is shown as well as the performance with respect to the timing of specific lower-tropospheric weather events. Moreover, it is discussed whether and how far the reanalysis products are superior over the “simple” downscaling products.”

Section 4


based on 250 hPa stream function data, over South Pacific and a center of action on the southeastern South America, JRA55 shows only reversal signs over South Pacific, from tropical to middle latitudes. Considering the original values, NCEP-NCAR reanalysis I shows the strongest anomalous signs in the three PDO phases for both wind and geopotential height, while JRA55 shows the weakest anomalies. Beside the anomaly intensity, the position of the strongest anomalies changes accordingly the reanalysis dataset.

In all the three PDO phases, JRA55 zonal wind anomalies at low levels show a westward displacement of the strongest negative and positive sign placed at the northern South America in relation to the NCEP-NCAR and the ERA40 reanalysis. Also, the opposite sign placed over the equatorial eastern Pacific westward of the strongest anomaly observed in the NCEP-NCAR and ERA40 datasets of the low level zonal wind anomaly in the northern South America is not observed in the JRA55 data.

This aspect in the low level zonal wind anomaly is observed both for positive and negative PDO phases, constituting an important distinction since it is observed throughout the whole analysed period.

South America climatic impact during PDO phases based on NCEP-NCAR reanalysis I, JRA55 and ERA40

Author Maria Elisa Siqueira Silva

Affiliation Univerty of São Paulo

Co-authorCarlos Batista Silva

The South America climatic behavior on reversal Pacific Decadal Oscillation, PDO, phases, from 1970 to 2003, is analyzed in this study through composite anomaly fields and the EOF technic. We used the reanalysis I of NCEP-NCAR, ERA40 and JRA55 reanalysis datasets. Considering geopotential height and wind variables, at low and high levels, all the three datasets present reversal climatic patterns on distinct PDO phases (1970-1976, 1977-1996, 1997-2003), with different intensities.

Although the three first EOF modes obtained from the 850 hPa stream function show very similar spatial patterns over South Pacific and South America in the three considered reanalysis, it is possible to notice some important differences among the original values. At 250 hPa, NCEP-NCAR reanalysis I and ERA40 stream function 3rd EOF modes agree very well while JRA55 presents great differences in relation to these other two datasets. While NCEP-NCAR reanalysis I and ERA40 3rd EOF modes show a well characterized mean wave train pattern,

the impact of the atmospheric forcing appears only marginal for the global heat content estimates in both upper and deeper oceans.

A sensitivity assessment performed through realistic perturbation of the main sources of uncertainty in ocean reanalyses highlights that bias-correction and pre-processing of in-situ observations represent the most crucial component of the reanalysis, whose perturbation accounts for up to 60% of the ocean heat content anomaly variability in the pre-Argo period.

These results reveal useful information for the ocean observation community and for the optimal generation of perturbations in ocean ensemble systems. Additional information on the dependence of the quality of ocean reanalyses from atmospheric products are also presented.

Considerable disagreement is found for the other straits and transport types, which must be investigated further. The net export of volume out of the Arctic Ocean derived from ARCGATE is – 0.15 ± 0.06 Sv. This value is matched by ORAS5 very well (- 0.14 ± 0.18 Sv), while C-GLORS net volume export is only about one third of the ARCGATE estimate (- 0.05 ± 0.22 Sv).

Sensitivity of ocean heat content from reanalyses to the atmospheric reanalysis forcing: a comparative study


Affiliation CMCC

Co-authorsC Yang (CNR-ISAC), S Masina

The global ocean heat content evolution is a key component of the Earth’s energy budget and can be accurately determined by ocean reanalyses that assimilate hydrographic profiles. This work investigates the impact of the atmospheric reanalysis forcing through a multi-forcing ensemble ocean reanalysis, where the ensemble members are forced by five state-of-the-art atmospheric reanalyses during the meteorological satellite era (1979-2013).

Data assimilation leads the ensemble to converge towards robust ocean heat content estimates and significantly reduces the spread (1.48 +/- 0.18 W/m2, per unit area of the World Ocean); hence

Section 4


the observed trends and not with those from climate models (e.g. Monge-Sanz et al., 2012; Diallo et al., 2012; Ploeger et al., 2015). To increase our confidence in climate-chemistry projections, the causes for the apparent disagreement in trends of age-of-air between observations and most climate models need to be identified.

When evaluating different reanalysis products it is important to know, to the possible extent, what differences among datasets are due to the differences in the underlying numerical models, and what differences are due to the assimilated datasets of observations.

That is why in this study we have carried out simulations with a CTM to assess the stratospheric circulation with the ERA-Interim dataset, as well as with data produced from an equivalent climate system. AoA trends from our model results with ERA-Interim fields are in good agreement with the recent age-of-air studies based on observations and differ from the results we obtain with the corresponding climate data.

We will show that biases in the mean AoA values are also different for these datasets compared to observations. In addition we have used recent experimental datasets from the ECMWF system to identify potential causes for the differences in AoA distribution and trends. The validation of our model results has been performed against the new revised AoA dataset based on MIPAS SF6 observations (Haenel et al., 2015).

Stratospheric trends: Reanalysis v. climate models

Author Beatriz Monge-Sanz

Affiliation ECMWF

Co-authorsD. Dee (ECMWF), H. Hersbach (ECMWF), A. Simmons (ECMWF), J. A. Parodi (AEMET), P. Hitchcock (NCAR), F. Haenel (KIT), G. Stiller (KIT), M. P. Chipperfield (U. Leeds), W. Feng (U. Leeds)

In the framework of the SPARC Reanalyses Intercomparison Project (SRIP), we are evaluating the main reanalysis products of the world (Fujiwara et al., 2017) with a particular focus on their ability to reproduce stratospheric processes.

In the present study we focus on the Brewer-Dobson circulation (BDC), the major circulation pattern in the stratosphere. Most climate models have predicted an intensification of the stratospheric circulation with the increase in greenhouse gases concentrations, which translates into younger age-of-air (AoA) values modelled in the stratosphere. Nevertheless, balloon and satellite observations do not agree with the widespread modelled trend towards younger age-of-air for the recent past (Engel et al., 2009; Stiller et al., 2012; Haenel et al. 2015).

Furthermore, a few recent studies with chemistry transport models (CTMs) driven by ERA-Interim reanalysis (Dee et al., 2011) have also shown agreement with

products cover large parts of the NH, but have problems with large solar zenith angles as well as over complex terrain (eg. Wang et al. 2014).

Our analysis focuses at the Russian territory where we utilize in-situ radiation and snow depth measurements. We found 50 stations which measure both variables on a daily basis for the period 2000-2013. Since Hall (2004) found that 50% of the notal NH snow albedo feedback caused by global warming occurs during NH spring, we focus on the transition period of March to June (MAMJ). Here we use custom ERA-Interim land configurations with different vegetation settings to compare in-situ data to gridded products in respect to albedo and snow depth properties on daily and seasonal scales.

We found a very good representation of daily snow variability and small absolute errors among different reanalyses. However, due to vegetation parameters, albedo in reanalyses shows substantially lower variability than in stations. For this, significant improvement was found between stations and grass-only configurations of ERA-Interim land. Finally, snow albedo feedbacks in stations and grass-only configurations are naturally higher than in “realistic” configurations of ERA-Interim.

Spring snow albedo feedback in daily data over Russia. Analyzing in-situ data in comparison with reanalyses

Author Martin Wegmann

Affiliation University of Grenoble

Co-authorsO. Zolina (Institut des Géosciences de l’Environnement, University of Grenoble, Grenoble, France and P.P. Shirshov Institute of Oceanology, Moscow, Russia), H.-W. Jacobi (Institut des Géosciences de l’Environnement, University of Grenoble, Grenoble, France), E. Dutra (Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal)

Global warming is enhanced at high northern latitudes where the Arctic surface air temperature has risen at twice the rate of the global average in recent decades – a feature called Arctic amplification. This recent Arctic warming signal likely results from several factors such as the albedo feedback due to a diminishing cryosphere, enhanced poleward atmospheric and oceanic heat transport, and changes in humidity.

Surface albedo feedback is stating that the additional amount of shortwave radiation at the top of the atmosphere decreases with decreasing surface albedo whereas surface air temperature increases with decreasing surface albedo. Unfortunately, there remains a lack of reliable observational data over large parts of the cryosphere. Satellite

Section 4


This analysis shows that the assimilation of surface fields apparently introduces some spurious trends in the HC, enhancing its multi-decadal and long-term variability. Its effect is particularly strong on Southern HC, where its strengthening is only supported by ERA-20C and it is inconsistent with the projected weakening of the tropical circulation. Assimilating surface pressure and winds weakens the dynamical link between Southern HC extent and meridional temperature gradient and extratropical tropopause height in Southern Hemisphere, rising inconsistencies among ERA-20CM and ERA-20C. Further, the analysis is extended to the ECMWF reanalysis ERA-Interim, for the period 1979-2010, where these correlations are found not to be statistically significant. On this respect it appears that ERA-20CM produces a more consistent evolution of the HC than ERA-20C and data assimilation weakens dynamical links that would otherwise be present in model simulations.

The effect of the data assimilation on Hadley Circulation variability and trends in the 20th century

Author Roberta D’Agostino

Affiliation Max Planck Institute for Meteorology

Co-authorP. Lionello (University of Salento and CMCC)

The effect of the data assimilation on Hadley Circulation (HC) and ITCZ variability has been investigated through the comparison of trend magnitudes among ERA-20CM and ERA-20C. ERA-20CM is a 10-member atmospheric model integration forced by 10 different realisations of prescribed sea surface temperature (HadISST2.1) and sea-ice cover.

It is meant to provide a statistical estimate of the climate evolution and a good description of the low-frequency variability of the atmosphere during the 20th century without assimilating any atmospheric observations. ERA-20C is a deterministic reanalysis based on the same atmospheric model of ERA-20CM and forced by the same prescribed HadISST2.1 of the first member of the ERA-20CM ensemble. Furthermore, it assimilates marine surface winds and surface and mean sea level pressure.

currently developed with that same NEMO model grid (ORCA025 at 1/4°) to propose a multi-model ensemble product. Four reanalyses are used; GLORYS2V4 from Mercator Océan (Fr), ORAS5 from ECMWF, FOAM/GloSea from Met Office (UK), and C-GLORS from CMCC (It). The four different time series of global ocean monthly estimates have been post-processed to create the new product called GREP (Global Reanalysis Ensemble Product), covering the recent period during which altimetry observations are available: 1993-2015.

The ensemble mean and standard deviation of the ensemble, as well as the four individual members for the period 1993-2015, are thus made available on a 1°x1° grid and monthly frequency. The time series will be extended by one year each year. In this presentation, and in a series of companion posters, the ensemble mean performance will be compared to that of the individual members, with respect to satellite and in situ observations, and with 3D temperature and salinity estimates deduced from observations with statistical methods.

Surface currents, heat and mass transports, western boundary currents variability, and tropical oceans variability (El Niño, Atlantic and Indian ocean dipoles) deduced from GREP will be shown in this presentation. We will explore, following Xue et al (2017, DOI: 10.1007/s00382-017-3535-y), the possibility to use the spread in between individual members in order to highlight robust signals.

The Copernicus Marine Service Global Reanalysis Ensemble Product GREPV1: deriving robustness estimates for ocean currents and transports

Author Marie Drévillon


Co-authorsClément Bricaud (Mercator Océan), Yann Drillet (Mercator Océan), Karina von Schuckmann (Mercator Océan), Gilles Garric (Mercator Océan), Simona Masina (CMCC), Andrea Storto (CMCC), Laura Jackson (UK Met Office), Drew Peterson (UK Met Office), Richard Wood (UK Met Office), Hao Zuo (ECMWF), Magdalena Balmaseda (ECMWF), Stéphanie Guinehut (CLS), Sandrine Mulet (CLS), Jérôme Gourrion (Coriolis), Laurent Parent (Mercator Océan), Charly Régnier (Mercator Océan), Charles Desportes (Mercator Océan)

During the MyOcean project, several high resolution (1/4° horizontal grid) ocean reanalyses based on the NEMO numerical ocean model and constrained by satellite observations and in situ T and S profiles, were produced with different tunings and by different institutes, and were evaluated jointly using common validation guidelines (Masina et al, 2015, DOI: 10.1007/s00382-015-2728-5).

The Copernicus Marine Environment Monitoring Service CMEMS (marine.copernicus.eu) now takes advantage of the diversity of ocean reanalyses

Section 4


free ocean scale the trend estimates among long-term data records were generally found to be significantly different. Maxima in standard deviation among the data records are found over, e.g., tropical rain forests. These and other noticeable regions coincide with maxima in mean absolute differences among trend estimates.

These distinct features can be explained with break points which manifest on regional scale and which typically do not appear in stability analysis relative to ground-based observations. Results from profile inter-comparisons will also been shown and exhibit, among others, that the observed break points are not only a function of region but also of parameter.

The GEWEX Data and Assessments Panel (GDAP) has initiated the GEWEX water vapor assessment (G-VAP) which has the major purpose to quantify the current state of the art in water vapour products (upper tropospheric humidity, specific humidity and temperature profiles as well as total column water vapour) being constructed for climate applications.

In order to support GDAP and the general climate analysis community G-VAP intends to answer, among others, the following questions:a) How large are the differences in observed temporal changes in long-term data records of water vapour on global and regional scales?b) Are the differences in observed temporal changes within uncertainty limits?c) What is the degree of homogeneity (break points) of each long-term data record? A general overview of G-VAP will be given. The focus of the presentation will be on observed inconsistencies among long-term data records (eleven TCWV data records and seven specific humidity and temperature profile data records, six of which are based on reanalysis).

The inconsistencies are observed by inter-comparisons, comparisons to in-situ observations and the stability analysis. On basis of consistently applied tools major differences in state-of-art CDRs have been identified, documented and to a large extend explained. The results and the answers for TCWV are summarized as follows: On global ice-

The Rs from reanalyses have larger uncertainties, because their cloud fields were based on the model’s simulations in the reanalysis systems. Finally, ground-based observations of Rs and CERES EBAF Rs have been used to evaluate simulations of global climate models.

The GEWEX water vapor assessment (G-VAP) – results from inter-comparisons and stability analysis

Author Karsten Fennig


Co-authorsMarc Schröder (DWD, Offenbach, Germany), Maarit Lockhoff (DWD, Offenbach, Germany), Lei Shi (NOAA/NESDIS/NCEI, Asheville, USA)

A large variety of water vapour data records is available to date. Without proper background information and understanding of the limitations of available data records, these data may be incorrectly utilised or misinterpreted. The overall goal of assessments of CDRs is to conduct objective and independent evaluations and inter-comparisons in order to point out strengths, differences and limitations and, if possible, to provide reasons for them. The need for such assessments is part of the GCOS guidelines for the generation of data products.

The evaluations of surface incident solar radiation among reanalyses, satellite retrievals and ESMs

Author Ma Qian

Affiliation BNU

Co-authorsKaicun Wang (Beijing Normal University), Martin Wild (Institute for Atmospheric and Climate Science)

A best effort was made to collect ground-based measurements of surface incident solar radiation (Rs). However, the distribution of observations is still deficient on a global scale. Alternatively, satellite Rs retrievals, which employ sophisticated atmospheric radiative transfer models with satellite observations of cloud and aerosol parameters used as input, can provide globally gridded values of Rs.

Two sets of satellite retrievals of Rs from CERES EBAF and GEWEX-SRB (WCRP/GEWEX Surface Radiation Budget), were compared with Rs values from ground-based observations. Furthermore, two reanalyses from ERA-Interim and MERRA (Modern Era Retrospective Analysis for Research and Applications) were evaluated with ground-based observations. It shows that the CERES EBAF Rs has a better comparison with the ground-based observations among the latest satellite retrievals and reanalyses.

Section 4


reanalysis efforts and published 6-hour and monthly data in the Earth System Grid Federation (ESGF).

The reanalysis data is presented in a similar way as the CMIP3 and CMIP5 archives, using standardized Climate and Forecast (CF)-compliant variable names and consistent metadata. Along with easy access, CREATE’s processing and interface enable comparing multiple reanalysis data sets with each other and with climate and weather model output. The data is published one variable per file on the native horizontal grid and in vertical pressure levels.

An ancillary project has produced a similar product of the temperature, salinity, and velocity fields for the major ocean reanalyses. In addition to the native grids, the ocean reanalyses are also regridded to a common vertical and horizontal grid. The ESGF data interface is widely accepted throughout the international climate research community and provides a variety of tools for access. Procedures for downloading, viewing, and manipulating the data will be demonstrated.

All correlations are stronger in the boreal winter while in summer they become not significant with both ψN and ψS. In ERA-20C and in ERAInterim there is a correlation between total precipitation in the deep tropics and values of CE and ψN, whereas the correlation with NE and SE becomes not significant and vanishes in boreal summer. Further, the correlation between CE, NE, SE and the position of the precipitation maximum located near the Equator and north and south hemisphere precipitation minima, respectively are investigated. In ERA-20CM the correlations are significant only in the boreal winter, in ERA-20C the correlations remains significative only for the CE and SE and in ERAInterim only for the SE. All these outcomes suggest that data assimilation reduces a dynamical link that would otherwise be present in the atmospheric circulation model

The NASA/NCCS Collaborative Reanalysis Technical Environment

Author Gerald Potter

Affiliation NASA/GFSFC

Co-authorsL. E. M. Carriere (NASA/GSFC), J.A. Hertz (NASA/GSFC)

In order to simplify access to multiple reanalyses, the NASA/NCCS Collaborative REanalysis Technical Environment (CREATE) has repackaged selected fields from the world’s major

The link between the tropical precipitation and Hadley circulation: comparing ECMWF reanalysis ERA-20C and ERA-Interim to the AMIP-like experiment ERA-20CM

Author Ascanio Luigi Scambiati

Affiliation Università del Salento

Co-authorsR. D’Agostino (MPI), P. Lionello (University of Salento, CMCC)

This contribution investigates the reproduction of the link between intensity of zonally averaged tropical precipitation and Hadley Circulation (HC) width and intensity in ECMWF ERA-20C and ERAInterim at seasonal scale. The reanalyses are compared to the ERA-20CM (AMIP-experiment) data. The HC monthly mean mass stream function ψ is computed and the HC Central Edge (CE), the Northern Edge (NE) and the Southern Edge (SE) are defined as the zero-crossing latitudes of ψ bulk, where ψ bulk is the average of ψ between 150 and 700 hPa.

The strength of the HC is given by the maximum and minimum values of ψ in the Northern Hemisphere (ψN) and Southern Hemisphere (ψS), respectively. In ERA-20CM results show a large correlation between the total precipitation in the belt 10°N – 10°S (deep tropics) and values of NE, SE, CE as well as with ψN, while correlation between the total precipitation and ψS is weaker.

The importance of reanalysis monitoring: the example of ERA5

Author Andras Horanyi

Affiliation ECMWF

Co-authorsP. Berrisford (ECMWF), G. Biavati (ECMWF), H. Hersbach (ECMWF), J. Muñoz-Sabater (ECMWF), C. Peubey (ECMWF), R. Radu (ECMWF), I. Rozum (ECMWF), D. Schepers (ECMWF), A. Simmons (ECMWF), C. Soci (ECMWF)

The ERA5 reanalysis (implemented by the Copernicus Climate Change Service on behalf of the European Commission) is in production at the European Centre for Medium-Range Weather Forecasts (ECMWF). The scientific validation of the particular model version used is followed by the routine monitoring of the production suites of the system. The monitoring activity is focusing on the observation usage of the system as compared to ERA-Interim and ECMWF operations, the observation departures from the first guess and the analysis and on the analysis increments and differences as compared to other reanalysis systems at ECMWF.

The presentation will provide a brief overview of the monitoring tools used for ERA5 and an insight into how the monitoring activity is organised. Some examples will be shown focusing on when monitoring proved to be essential to detect problems and deficiencies of the ERA5 production suites.

Section 4


land, the unglaciated terrestrial surface, and sea ice/ocean. An examination is conducted of contemporary global reanalyses of the ECMWF Interim project, NASA MERRA, MERRA-2, JRA-55, and NOAA CFSR using available in situ data and assessments of the surface energy budget. Overly-simplistic representations of the Greenland Ice Sheet surface are found to be associated with local warm air temperature biases in winter.

A review of progress made in the development of the MERRA-2 land-ice representation is presented. Large uncertainty is also found in temperatures over the Arctic tundra and boreal forest zone. But a key focus of temperature differences for northern high latitudes is the Arctic Ocean. Near-surface air temperature differences over the Arctic Ocean are found to be related to discrepancies in sea ice and sea surface temperature boundary data, which are severely compromised in current reanalyses. Issues with the modeled representation of sea ice cover are an additional factor in reanalysis temperature trends. Differences in the representation of the surface energy budget among the various reanalyses are also reviewed.

and following the peak values. While the model represents these variations in general, regional strengths and weaknesses can be identified.

Understanding Arctic surface temperature differences in reanalyses

Author Richard Cullather

Affiliation ESSIC/University of Maryland at College Park

Co-authorsB. Zhao (Global Modeling and Assimilation Office, NASA Goddard Space Flight Center), C.A. Shuman (Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland), S.M.J. Nowicki (Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland)

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. For example, the 1980-2009 mean surface air temperature for the north polar cap (70°N-90°N) among global reanalyses span a range of 2.4 K, which approximates the average warming trend from these reanalyses over the 30-year period of 2.1 K.

Understanding these differences requires evaluation over the three principal surface domains of the Arctic: glaciated

Tropical Energy Variability in MERRA-2 and M2AMIP



Co-authorF.R. Robertson (NASA MSFC)

Studies have shown the correlation and connection of surface temperatures across the globe, ocean and land, related to Tropical SSTs especially El Niño. This climate variability greatly influences regional weather and hydroclimate extremes (e.g. drought and flood). In this paper, we evaluate the relationship of temperatures across the tropical oceans and continents in MERRA-2, and also in a newly developed MERRA-2 AMIP ensemble simulation (M2AMIP).

M2AMIP uses the same model and spatial resolution as MERRA-2, producing the same output diagnostics over 10 ensemble members. Composite El Niño temperature data are compared with observations to evaluate the land/sea contrast, variations and phase relationship. The temperature variations are related to surface heat fluxes and the atmospheric temperatures and transport, to identify the processes that lead to the lagged redistribution of heat in the tropics and beyond.

Discernable cloud, radiation and data assimilation changes accompany the onset of El Niño affecting continental regions through the progression to

The role of stratospheric dynamics on the climate system in response to Antarctic ozone trends: CMIP5 versus Reanalyses

Author Chiara Cagnazzo

Affiliation ISAC-CNR

Co-authorsG. Rea (ISAC-CNR), F. Fierli (ISAC-CNR)

In this work we analyze how CMIP5 models represent the stratospheric dynamics and specifically the lower stratospheric cooling observed in summer since 1979 to 2001 over Antarctica, an important aspect associated the austral springtime ozone hole. We find that models with a well-resolved and a chemical representation of the stratosphere better represent the lower stratospheric cooling, when compared to reanalyses.

However, there is a large range of trends among reanalysis data sets. Here we use reanalyses to estimate uncertainties in the observed trends and we use models to assess information about the quality of reanalyses trends.

Section 4


In particular we assess changes in the AMOC strength as observed by the RAPID array, changes in Atlantic ocean heat content and changes in North Atlantic convection.

Validation of reanalysis against variability and trends of in situ stations temperature time-series in the western half of Iran

Author Piero Lionello

Affiliation University of Salento

Co-authorsS. Sadrafshari Zanjan University, Iran), L. Scarascia (CMCC, Italy)

Iran appears to be a critical host spot of climate change. In fact, it is located in the central part of a stripe going from the Arabian Peninsula to the Eurasian steppe characterized by steep increase of temperature in the second half of the 20th century. Here we investigate to which extent the ERA-Interim (the continuously updated ECMWF 1979-to-present reanalysis), ERA20C and 20CR (ECMWF and NOAA ESRL 20th century re-analyses) reproduce the temperature behavior during the period 1979-2010 that is recorded at 15 meteorological stations in the western half of Iran.

Results are not free of problems. For all stations ERA-Interim and Era 20C are systematically biased low with respect to observations, while 20CR biases are locally large, but with different signs in different parts of the area, so that the

Using a multi-model ensemble of ocean reanalyses to understand recent changes in the North Atlantic ocean.

Author Laura C. Jackson


Co-authorsC. Dubois (Mercator ), L.C. Allison (Met Office), K.A. Peterson (Met Office)

The observational network around the North Atlantic has improved significantly over the last few decades with the advent of ARGO and satellite observations, and the more recent efforts to monitor the Atlantic Meridional Overturning Circulation (AMOC) using arrays such as RAPID and OSNAP. These have shown decadal timescale changes across the North Atlantic including in heat content, heat transport and the circulation.

However there are still significant gaps in the observational coverage, and significant uncertainties around some observational products. Ocean reanalyses integrate the observations with a dynamically consistent ocean model and are potentially tools that can be used to understand the observed changes, however the suitability of the reanalyses for the task must also be assessed. We use an ensemble of global ocean reanalyses in comparison with observations in order to examine recent changes in the North Atlantic.

is the unprecedented reduction of Indonesian Throughflow (ITF) volume (-20%) and associated heat transport (-25%) during 2015/16. Although weakening of the ITF is typical for El Niño events, the amount of heat retained in the Pacific by reduced ocean energy export was exceptional during 2015/16 and explains 83% of the found difference in OHC changes.

The reduction of the ITF transports was related to the observed strong warming of the eastern Indian Ocean in recent years, which enhanced anomalous sea level gradients across the Indo-Pacific Warm Pool. Increased absorption of solar radiation consistent with positive SST anomalies prevailing in the eastern subtropical Pacific was a secondary effect damping the tropical pacific OHC discharge.

As a result, the 2015/16 El Niño left the Pacific in a state recharged for the occurrence of another El Niño event, only two years after the previous one. This conclusion is supported by seasonal prediction systems that – at the time of writing – indicate the possibility of another El Niño event for the winter 2017/18.

Unprecedentedly weak Indonesian Throughflow during 2015/16 speeds up Tropical Pacific heat recharge after El Niño

Author Michael Mayer

Affiliation ECMWF

Co-authorsM.A. Balmaseda (ECMWF), L. Haimberger (Univ. Vienna)

The 2015/16 El Niño event exhibited peak sea surface temperature (SST) anomalies similar to the record-breaking 1997/98 event. Here we employ atmosphere and ocean reanalyses from ECMWF (ORAS4, ORAS5, ERA-Interim) and JMA (JRA-55) in conjunction with satellite data (CERES-EBAF) to compare anomalous energy flows through the climate system during these two El Niños.

This perspective is only possible thanks to the revolution on the ocean observing systems and analysis capabilities in real time. We show that despite its extreme surface characteristics, there was no longer lasting cooling of tropical Pacific subsurface waters associated with the 2015/16 El Niño.

In fact, tropical Pacific upper ocean heat content (OHC) at the end of 2016 was higher than at the beginning of 2015 by about 7.1±0.5 ZJ, which is in stark contrast to statistical expectation and previous big El Niño events like that in 1997/98 (-15.7±4.3 ZJ OHC loss). The main reason for this surprising result

Section 4


Visual analysis



One of the strengths of reanalyses is in their detail – they describe the complex structure of the atmosphere, showing the behaviour of many variables on a range of space and time scales. This strength makes them difficult to appreciate and inter-compare – it is hard to capture their value and accuracy in simple numerical metrics.

Modern scientific visualisation methods offer a powerful tool for analysis and comparison. Careful choice of colour and structure allows plots capturing spatial detail for several variables simultaniously, and video shows their time-evolution.

Observed wave spectra characteristic parameters were compared with the ones simulated through the regional numerical propagation wave model SWAN with a 20 meter resolution allowing to investigate the model reliability such as the robustness of the boundary conditions. The results show a good agreement between observed and simulated wave data with mean square error and bias for the significant wave height of 0.3 and 0.2, respectively. As for the peak period, a mean square error and a bias of 1.9 and 0.8 seconds were instead calculated. Low frequency wave energy coming from E-ESE and SES-S bins presents the highest mean square error in the spectra. This is due to the Arvoredo Island which creates a diffraction pattern that causes a wrong estimate of the peak direction, highlighting the importance of a multimodal wave spectra identification.

Validation of the SWAN model with wave spectra observation in the Arvoredo marine biological reserve, Santa Catarina, Brazil

Author Pietro Albano

Affiliation BMingegneria

Co-authorsDavide Franco (Lahimar-UFSC), Alejandro Donnangelo (Lahimar-UFSC)

This study provides a comparison between wave observations in shallow water and wave data simulated through the SWAN model, forced in deep water by Hindcast reanalysis directional wave spectra of the WW3_NOOA model. From March 2014 until April 2016, within the MAArE project, it has been possible to characterize the wave regime in the marine biological reserve of Arvoredo, situated 11 Km north of the island of Florianopolis, in the south Brazilian shore.

The two years survey was carried out by an Acoustic Doppler Profiler (ADP) located at a depth of 21 meters and it allowed to analyse the directional wave spectra characteristic parameters through the extended maximum entropy method (Haschimoto et al., 1994). Local wave regime mainly showed east seas with a period between 6 and 8 seconds and significant wave height between 0.5 and 1 meter.

overall bias is actually smaller than the two other datasets. Correlation between re-analyzes and observed time series has in general a seasonal connotation, with low values in summer and high values in winter.

For almost all stations ERA-Interim presents the largest correlation among the three datasets. However, considering trends, there is a large discrepancy between the small values of 20CR (with annual values close to 2K/century) and the very large trends of ERA20C and ERA-Interim (around 6.5 and 8.5K/Century, respectively). CRU trends are large as well (slightly below 6K/Century) and much closer to trends in ERA20C and ERA-Interim than to 20CR.

Differences among trends are mostly related to the two last decades of the 20th century, when the behavior of ERA-Interim and ERA20C has been characterized by a very large negative bias with respect to observations, which has been decreases rapidly (without anyway vanishing) afterwards. On the contrary, ERA20C time series show a flatter behavior than other datasets during the whole period.

Section 4


progression that fills the needs of the community and contributes to the WCRP mission. The primary charge to the TIRA is to develop a reanalysis intercomparison project plan that will attain the following objectives.

1) To foster understanding and estimation of uncertainties in reanalysis data by intercomparison and other means.

2) To communicate new developments and best practices among the reanalyses producing centers.

3) To enhance the understanding of data and assimilation issues and their impact on uncertainties, leading to improved reanalyses for climate assessment.

4) To communicate the strengths and weaknesses of reanalyses, their fitness for purpose, and best practices in the use of reanalysis datasets by the scientific community This presentation outlines the need for a task team on reanalyses, their intercomparison, the objectives of the team and progress thus far.

WCRP Task team for the Intercomparison of ReAnalyses (TIRA): Motivation and Progress



Co-authorsTIRA Member

Reanalyses have proven to be an important resource for weather and climate related research, as well as societal applications at large. Several centers have emerged to produce new atmospheric reanalyses in various forms every few years. In addition, land and ocean communities are producing disciplinary uncoupled reanalyses. Current research and development in reanalysis is directed at (1) extending the length of reanalyzed period and (2) use of coupled Earth system models for climate reanalysis.

While WCRP’s involvement in the reanalyses communities through its Data Advisory Council (WDAC) has been substantial, for example in organizing international conferences on reanalyses, a central team of reanalyses expertise is not in place in the WCRP structure. The differences among reanalyses and their inherent uncertainties are some of the most important questions for both users and developers of reanalyses.

Therefore, a collaborative effort to systematically assess and intercompare reanalyses would be a logical

Section 4


This creates a temporally and spatially varying ELR, that can be used to downscale near-surface air temperature from the reanalysis resolution to higher resolutions. This approach could replace the commonly used global constant ELR of 6.5 K km-1 by an ELR based on local meteorological conditions.

The ELR estimates based on ERA5 and ERA-Interim were compared with observationally based ELR over the U.S. using the GHCN temperature data, showing a good agreement. The method is used to downscale ERA5 to about 9 km globally and validated against in-situ temperature observations and compared with simulations without any topographic correction and with a constant ELR.

The results suggest some benefits of using this new ELR over complex terrain regions, when compared with a constant value, and suggest that this new methodology could be used as a default for downscaling temperature from reanalysis on the global/regional scale where local in-situ observations are scarce and computational resources limit dynamical downscaling.

A temporally and spatially varying environmental lapse-rate for temperature downscaling

Author Emanuel Dutra

Affiliation Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa

Co-authorsJ. Muñoz-Sabater (2), S. Boussetta (2), T. Komori (3), S Hirahara (3), and G. Balsamo (1). 1: Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, 2: European Centre for Medium-Range Weather Forecasts, 3: Global Environment and Marine Department, Japan Meteorological Agency

Temperature near the surface varies with altitude accordingly to the environmental lapse-rate (ELR). The ELR depends on the overlying air masses, large-scale situation and local effects. The characterisation of the ELR has several applications, in particular to downscale global/regional numerical weather predictions, and reanalysis in complex terrain regions.

From an observational point of view, complex terrain regions also constitute a challenging environment due to the difficulties associated with the installation and maintenance of observational networks. In this study we propose the derivation of the ELR from the reanalysis lower troposphere vertical profiles of temperature.

The model simulation capability of the precipitation and the vortex moving path using different initial conditions are compared, the impact on the structure evolution character of SWCV by assimilating intensive sounding data and its influence mechanism are analyzed.

The result shows: the forecast capability of precipitation and the moving path of plateau vortex(PV) and SWCV are improved by assimilating both intensive sounding data and the conventional data, a worse forecast is produced by assimilating operational sounding data individually; by introducing intensive sounding data, the strength of initial plateau vortex(PV) and SWCV are enhanced due to the increase cyclonic perturbation on the initial wind field, besides, the more unstable stratification adjusted by data assimilation makes the model more easy to produce large precipitation in initial times as the observation’s magnitude.

The experiment reveals the generation and maintenance of SWCV on 700hPa in this case is not rely on high potential vorticity on upper air, it must need positive vorticity transported by the enhanced vertical movement which caused by latent heat release of precipitation condensation.

Section 5 – Applications of reanalyses

A numerical study on Southwest China Vortex (SWCV) scientific experiment data assimilation in a heavy rainfall event caused by vortex and its influencing mechanism

Author Duming Gao

Affiliation Institute of Plateau Meteorology, China Meteorological Administration (CMA)

Co-authorsYueqing Li (Institute of Plateau Meteorology, China Meteorological Administration (CMA))

Based on the Weather Research Forecast(WRF) model and WRF data assimilation system(WRFDA), an sensitivity analysis is conducted in a data assimilation experiment using operational sounding data and the intensive observed data of Southwest China vortex(SWCV) scientific experiment on a heavy rainfall caused by vortex in Sichuan Basin.


mainly between 1994 and 2009. Using meteorological stations data of near sub-basins and data from the NCEP Reanalysis database, the trends of the increase of the temperatures showed values of 1 °C in the reference period and anomalies of 0.02 to 0.04 °C were described.

Through the thermal bands of the Landsat images and the application of the standard deviation of the temperature, it was determined that the area with the greater variation of temperature, between 2 and 4 °C, was located in the altitudinal range of 3600 to 4000 meters. The data obtained show an increase in temperature variability, which could be influencing an increase in the use of agricultural lands at higher altitudes in the Vilcabamba sub-basin. This situation would cause a change in the vegetation found naturally in the highlands, affecting ecosystem services that the area offers.

Analysis of possible effects of temperature change on the temporal and altitudinal dynamics of agricultural areas in the Andes of southern Peru

Author Alexis Nicolas Ibañez Blancas

Affiliation Centro de Investigaciones de Zonas Aridas

Co-authorsGrégry Damman (CIZA UNALM), Maria Fernanda de los Rios (CIZA UNALM)

The study of the effect of the temperature change on the dynamics of ecosystems is getting attention in a context of climate change. This effect may be more sensitive for mountain ecosystems, especially because of the altitudinal gradient. In the Peruvian Andes, having tropical mountains, the effect of temperature variation may be more easily observable. The present work aims to describe the dynamics of agricultural areas in the southern Peruvian Andes, in the Vilcabamba river basin, from 1986 to 2009. It also looks forward to explain the possible effects of temperature change on agricultural areas in the gradient between 2400 and 4000 meters.

With the use of Landsat and ASTER images, the land use changes in relation to height was modeled. It showed an increase on agricultural area use between the 3600 and 4000 m.a.s.l.,

None of the reanalysis datasets assimilate surface temperature data, but they differ in the data that are assimilated: both ERA-20C and 20CR assimilate surface pressure data; ERA-20C also includes surface wind data over the oceans; ERA-20CM does not directly assimilate any of these synoptic data. As such ERA-20CM is viewed as a form of control, in the sense that the data are not constrained by observed MSLP or marine wind data, as is the case with the other reanalyses. Most previous analyses of the annual cycle have only examined changes over the latter half of the twentieth century, but the century-long view afforded by these reanalyses has allowed us to examine trends in the annual cycle back to 1902.

It is demonstrated from the comparison of these datasets that much of the interannual to lower-frequency variability in the amplitude of the annual cycle is attributable to synoptic variability, with oceanic coupling being the critical factor. Furthermore, the variability in the phase and amplitude of the annual cycle during the post-1950 period was unusual in the context of the twentieth century, although uncertainty is greatest before ca. 1930 as a result of relatively sparse data coverage during across most regions of the northern hemisphere.

An assessment of trends in the annual cycle of temperature across the Northern Hemisphere

Author Richard Cornes

Affiliation KNMI

Co-authorsPhil Jones (Climatic Research Unit, University of East Anglia), Cheng Qian (CAS Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences; and University of Chinese Academy of Science)

The annual cycle of temperature accounts for more than 90% of the variance of surface air temperature across extra-tropical regions. Observations have indicated profound changes in the annual cycle throughout the twentieth century, but the factors influencing these trends remain poorly understood. In this analysis we evaluate these changes in the annual cycle through the comparison of four reanalysis datasets (ERA-20C, ERA-20CM and two versions of NOAA-20CR) against the CRU-TS dataset.

The Modulated Annual Cycle (MAC) is calculated from the data using Ensemble Empirical Mode Decomposition (EEMD), from which phase and amplitude metrics are derived.

Section 5


narrow channel approximately 450 km in width and 2600 km in length. The precipitation resulting from the inland penetration of this AR is also analyzed.

To consider this event in a climatological context, IWV and IVT data are derived from ECMWF for the month of February over the 20-year period from 1996-2015. Dates of observed landfalling ARs for water years (WYs) 1998-2008 that impacted the California coast (32.5N-41.0N) are obtained from SSM/I. Dates for February 1996-1997 and 2009-2015 are based on ECMWF with the constraint that IWV >20 mm for observations that are 12 hrs. apart.

It is observed that the February 2014 AR event is one of five significant events in the 20-year period, as measured by IWV >30 mm. An algorithm was developed to filter the raw data in order to meet a threshold of >20 mm (IWV) and >250 kgm-1s-1 (IVT) for a duration of >12 hrs. to expose values that represent AR events. A composite mean of the IVT values is also calculated, showing peak IVT of 500-600 kgm-1s-1 at the core of the composite AR.

Major issues in the reanalyses are underestimation of upper ocean stability and surface current in EIO and over estimation of vertical shear of current and variability of different physical oceanic variables. To improve the skill of reanalyses over the TIO, salinity vertical structure and upper ocean circulation need to be better represented.

Atmospheric River Event over the Eastern Pacific in February 2014: Analysis and Climatological Context

Author Deveshi Buch

Affiliation Vista del Lago High School

Atmospheric rivers (ARs) are narrow and intense plumes of water vapor that are known causes of heavy precipitation events. This is an analysis of the evolution, transport, and landfall of a significant AR event in February 2014 over the Eastern Pacific and West Coast of the United States, considered in a climatological context.

Integrated Water Vapor (IWV) and Integrated Vapor Transport (IVT) values are calculated based on NASA MERRA and ECMWF ERA-Interim reanalysis datasets. The AR is characterized by high levels of IWV (~29 mm) as well as IVT (~759 kgm-1s-1). Analysis of the synoptic-scale progression of upper-level extratropical cyclones and anticyclones shows the flow of vapor transport in a

Analysis of mean state of SST and sea surface salinity (SSS) reveals that ORAS4 is better comparable with observations/EN4 data, which is followed by SODA, ECDA and GODAS. The surface circulation in ORAS4 is closer to OSCAR compared to the other reanalyses. However mixed layer depth (MLD) is better simulated by SODA, followed by ECDA, ORAS4 and GODAS.

Seasonal evolution of error indicates that the highest deviation exists during spring and summer in SST and MLD over the TIO in GODAS. These errors may play very decisive role since GODAS (during spring) is widely used to initialize the coupled models for seasonal prediction of Indian summer monsoon. Statistical analysis with concurrent data of EN4 for the period of 1980-2010 supports that the difference and standard deviation (variability strength) ratio for SSS and MLD is mostly greater than one.

In general the strength of variability is over estimated by all the reanalyses. Further analysis with in-situ buoy observations supports that MLD errors over the equatorial Indian Ocean (EIO) and Bay of Bengal are higher than estimated with respect to EN4 data. Overall ORAS4 displays higher correlation and lower error among all reanalyses with respect to both EN4 data and buoy observations.

Assessment of different ocean reanalyses over the Tropical Indian Ocean

Author Ananya Karmakar

Affiliation Indian Institute of Tropical meteorology

Co-authorsPune- 411008, India, Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune -411007), Anant Parekh (Indian Institute of Tropical Meteorology (IITM), Pune- 411008, India), J. S. Chowdary (Indian Institute of Tropical Meteorology (IITM), Pune- 411008, India), and C. Gnanaseelan (Indian Institute of Tropical Meteorology (IITM), Pune- 411008, India)

This study makes an inter comparison of ocean state of Tropical Indian Ocean (TIO) in different ocean reanalyses such as Global Ocean Data Assimilation System (GODAS), Ensemble Coupled Data Assimilation (ECDA), Ocean Reanalysis System 4 (ORAS4) and Simple Ocean Data Assimilation (SODA) with reference to the in-situ buoy observations, satellite observed Sea Surface Temperature (SST), EN4 data, and ocean surface current analysis real time (OSCAR).

Section 5


more sever over the area which leads to flood, landslide and loss of many lives.

In the present study rainfall has been taken as the criteria for predicting the intensity and location of Mandi cloudburst using ANN approach, Input data to which was obtained by performing numerical simulation using the Weather Research and Forecasting (WRF) model. WRF model was configured with spatial resolution of 7km over three sites of cloudburst that is Uttarkashi (30.7268 N, 78.4354 E), Leh (34.1526 N, 77.5771 E) and Mandi (31.706 N, 76.93 E).

Different physics option and convection parameter with single domain for Uttarkashi, Leh and multiple nested 2 way domain for Mandi has been used to best simulate the event. Three different Neural network training was done using MATLAB with input data of Uttarkashi having 11 inputs and 89 samples, Leh having 11 input and 991 samples, Mandi having 11 inputs and 85 samples using Feed Forward Neural Network with Back Propagation algorithm.

Hyperbolic tangent sigmoid function at hidden layer and linear function at output layer was taken as the activated function for training the three networks. Number of hidden layers was decided using Kolmogorov’s theorem. Prediction was done at Mandi using three trained neural networks. Results are shown as the observed and predicted rainfall at 6hr time step.

However, few reanalyses capture the observed long-term PW changes, primarily because they show spurious wet biases before about 2002. This deficiency results mainly from the discontinuities contained in reanalysis RH fields in the mid-lower troposphere due to the wet bias in older radiosonde records that are assimilated into the reanalyses. Thus, more efforts are needed to remove spurious changes in input data for future long-term reanlayses.

Combination of WRF and ANN Model for predicting cloudburst

Author Abhishek Sharma

Affiliation Indian Institute of Technology Roorkee

Co-authorDr. Kamal Jain (Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee)

Himalayan states of India such as Himachal Pradesh and Uttarakhand are prone to cloudbursts, landslides and other catastrophic events due to its geographical structure. Severity of these events has a strong correlation with the orographic precipitation. On 8th August 2015 between 00 to 06 hr UTC, heavy and continuous rainfall lead to a cloudburst event over Mandi district of Himachal Pradesh.

The interaction of extensive monsoon flow and the elevated terrain makes the high rainfall event persistent as well as

changes in recent years in China, and it improves correlation of the precipitable water (PW) with precipitation and the spatial coherence of the PW trend during recent 40 years. The PW variations and changes are highly correlated with those in lower–midtropospheric mean temperature (r = 0.83), with a dPW/dT slope of ~7.6% K−1, which is slightly higher than the 7% K−1 implied by Clausius–Clapeyron equation with a constant relative humidity (RH).

The radiosonde data show only small variations and weak trends in tropospheric RH over China. Using these homogenized observations, the PW from the NCEP/NCAR, NCEP/DOE, MERRA, JRA-55, JRA-25, ERA-Interim, ERA-40, CFSR and 20CR reanalyses is evaluated for the period from 1979-2012 (1970-2001 for ERA-40).

Results suggest that the PW biases in the reanalyses are within ~20% for most of northern and eastern China, but the reanalyses underestimate the observed PW by 20%–40% over western China, and by ~60% over the southwestern Tibetan Plateau. The newer-generation reanalyses (e.g., JRA25, JRA55, CFSR and ERA-Interim) have smaller root-mean-square error (RMSE) than the older-generation ones (NCEP/NCAR NCEP/DOE and ERA-40). Most of the reanalyses reproduce well the observed PW climatology and interannual variations over China.

Changes of atmospheric precipitable water in observations and reanalysis over China

Author Tianbao Zhao

Affiliation Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS)

Co-authorAiguo Dai (Department of Atmospheric and Environmental Sciences, University at Albany, SUNY, Albany, New York, USA)

Radiosonde humidity data provide the longest record for assessing changes in atmospheric water vapor, but they often contain large discontinuities because of changes in instrumentation and observational practices.

In this study, the variations and trends in tropospheric humidity (up to 300 hPa) over China are analyzed using a newly homogenized radiosonde dataset. There are, however, many spurious changes and discontinuities in the raw radiosonde records resulting from changes in instruments, observational practice, processing procedures, station relocations, and other issues. Recently, the daily humidity records radiosonde derived from about 130 Chinese stations were homogenized using a new approach developed by Dai et al. (2011).

It is shown that the homogenization removes the large shifts in the original records of humidity resulting from sonde

Section 5


In summer, the OGWD obtained from the traditional scheme is generally confined in the lower stratosphere north of 30°N. In the new scheme the mid-latitude (about 30~60°N) OGWD is also mainly located in the lower stratosphere, while at high latitudes notable OGWD is found within a deep column of the stratosphere. In winter, both the new and old parameterization schemes produce OGWD in the whole stratosphere, especially in the upper stratosphere of high latitudes.

To sum up, the new parameterization scheme tends to give smaller OGWD in the lower stratosphere but larger OGWD in the mid-upper stratosphere. The difference between them mainly occurs over the Tibet Plateau, the Rocky Mountain, and the Greenland.

Comparison of two parameterization schemes of orographic gravity wave drag using the ERA-Interim reanalysis

Author Xin Xu

Affiliation Nanjing University

Co-authorYuan Wang (School of Atmospheric Sciences, Nanjing University)

Developed in early 1980s, the parameterization of orographic gravity wave drag (OGWD) is now implemented in nearly all the state-of-the-art general circulation models (GCMs) and chemistry climate models (CCMs). However, current OGWD parameterization schemes only consider the vertical propagation of orographic gravity waves (OGWs), while in reality these waves propagate both vertically and horizontally.

The lateral spread of OGWs can reduce the local wave amplitude with height, thereby giving rise to wave breaking and hence OGWD at higher altitudes. Using the Gaussian beam approximation (GBA) approach, a new OGWD parameterization scheme is proposed which explicitly deals with the horizontal propagation of OGWs. This new scheme is compared with the traditional scheme by examining the OGWD in the stratosphere of Northern Hemisphere during 2011-2016, using the ERA-interim reanalysis data produced at the European Center for Medium-Range Weather Forecasts (ECMWF).

all calendar months with the possible exception of August, for the period of the regional reanalysis (1995-2014).

The correlation coefficients between COSMO-REA6 and traditional monthly means from gridded station data are higher than 0.97 for most areas. Differences between the regional reanalysis and the gridded station data appear at Northern Germany, likely because of the lack of data coverage in the traditional method. More differences become apparent when reducing area size.

Discrepancies could be caused by various reasons, for instance by local influences on the station observations, or by a lack of the reanalyses to capture the processes observed at the stations. Here we show our results in attempting to distinguish between these options and the implications for trend analysis over Germany.

Comparing traditional climatological records with reanalysis time series over Germany

Author Andrea Kaiser-Weiss


Co-authorsM. Borsche (DWD), D. Niermann (DWD), F. Kaspar (DWD)

Traditionally, gridded station data are the basis to estimate climatological time series of, e.g., the development of mean temperature over Germany.

Here we compare this time series against the one derived from the regional reanalysis COSMO-REA6 as well as against the global reanalysis ERA-Interim. We focus on temperature observations performed 2m above ground. There are discrepancies in the statistical properties on scales from the hourly scale to the decadal scale. For the whole of Germany, the COSMO-REA6 annual cycle matches the traditionally derived one, allowing for a bias with annual cycle which is well-known for COSMO model.

The year-to-year variability is higher than the bias. Both reanalysis data and traditional data track the annual anomalies. For trend applications it is of interest whether the bias is constant over the decades. This can be confirmed for the annual mean over Germany and

Section 5


oil spill simulation results. The aim is to find the best wind inputs for optimal prediction of oil spills in the Persian Gulf. We will use the observed Mina Al-Ahmadi oil spill event for the Mike 21/3 model verification. The calibrated model will be at the core of a decision support system for oil spill management and coastal area protection in the Persian Gulf.

Estimation of hourly and daily clearness indices and diffuse fraction, over Port Harcourt and Kano Nigeria using NCEP/NCAR satellite data

Author Vincent Omole

Affiliation College of Education Ikere Ekiti Nigeria

Co-authorsB. Adeyemi, (Federal University of Technology Akure, Nigeria), O. Oloniyo, (Federal University of Technology Akure)

In this study, estimation of clearness index (KT = H/H0) and diffuse fraction (KD = HD/H) were calculated using available satellite data obtained from National Centre for Environmental Prediction (NCEP) and National Centre for Atmospheric Research (NCAR) data base covering a period of 10 Years (2005–2014) for Port Harcourt and Kano stations which are Coaster and Sahel regions respectively. Direct solar data and diffuse solar data collected were added to give the Global solar radiation.

allocation of resources, while minimizing the risks and costs (Keeney, 1982; Mata and Corchado, 2009).

Many studies develop methods, tools, and decision support systems to identify potential oil spill sites, support oil spill risk management, and reduce the adverse effect of oil spills (Mokhtari et al., 2015; Ko and Chang, 2010; Lehikoinen et al., 2012; Jolma et al., 2014; Juntunen et al., 2005). Soltanpour et al. (2013) studied the key factors influencing the movement of oil spill in the Persian Gulf, and found that wind was the most important factors. In marine environment the wind forcing data is obtained from surface (synoptic) station, satellite observation, or numerical atmospheric model. Model assimilation techniques are used to improve the wind model forecast. According to Jones (1999), meteorological forecasts of wind from numerical model can be used as input to oil spill simulation with same accuracy as field wind observations. Temporal variations in wind were more important than spatial variations, and a high temporal resolution of the wind should be used In the use of oil spill model for contingency planning and management, a stochastic simulation with multiple events is often used (Eliot et al. 2014).

The main goal is to test the effect of different types of wind forcing (constant wind, spatially variable wind, time variable wind) and wind input data on the simulated oil spill trajectory, and test which data inputs provide the best

The reliability of the forecast ensemble will be determined by validation using historical sets of hindcasts. The inherent uncertainty of seasonal WF was quantified by issuing probability statements about future observable outcomes based on current and past forecasts (hindcasts) and observations. The WF will be withdrawn from ECMWF throughout the project in order to update the information provided by the models namely in terms of irrigation management during the growing seasons.

Effect of wind forcing on oil spill simulation in the Persian Gulf

Author Sahar Mokhtari

Affiliation Ports and Maritime Organisation (I.R.Iran)

Co-authorJirí Kadlec

Oil pollution is a serious environmental problem with critical impacts on marine and coastal habitats, wildlife, fisheries and human activities (Allan et al., 2012; Fattal et al., 2010; Carson et al., 1992). For preventing future oil spill disasters and to develop optimal planning and management strategies in response to oil spill events, an environmental risk assessment with capacity to support decision making is needed (Fabbri, 1998; Assilzadeh and Gao, 2010). This requires identifying and prioritizing areas in the coastal zone where there is a need for an

ECMWF probabilistic forecasts for near-real-time monitoring of drought in the trans-boundary Prut River Basin

Author Vera Potopova

Affiliation Czech University of Life Sciences Prague, Department Agroecology and Biometeorol

The aim of this study is to validate a probabilistic methodology from the ECMWF (Centre for Medium-Range Weather Forecasts) for near-real-time drought monitoring and forecasting to optimization of crop irrigation management in the Prut River catchment. The trans-boundary Prut River Basin is one of the most drought vulnerable areas in the Republic of Moldova, Romania and Ukraine due to high water exploitation. This paper presents the research undertaken within the project IMDROFLOOD (http://imdroflood.meteoromania.ro).

Seasonal daily weather forecast (WF) of maximum and minimum temperatures and precipitation from the ECMWF were collected and downscaled for the different locations from upstream to downstream of the Prut River Basin. These forecasts were used to produce the ensemble operational seasonal predictions and constitute models inputs. Short (1-month) and medium (3 and 7-month) range WF were retrieved.

Section 5


This research examines the role that large-scale circulation plays in local storminess for the North Atlantic islands of Orkney and Shetland. Automatic Lamb classification is applied to twentieth century reanalysis data to typify large scale circulation patterns and calculate measures of storminess, which are then validated using observations from meteorological stations on the islands, obtained through the UK Met Office.

This research uses the ERA-20C (1900-2010) reanalysis dataset produced by the European Centre for Medium-Range Weather Forecast. Daily mean sea level pressure (MSLP) data was obtained at 0.125° x 0.125° resolution, to which the weather classification method was applied. By characterising the relationship between large-scale climate trends and regional weather patterns, this research adds to our understanding of contemporary changes in storminess on North Atlantic islands, and can thus aid in anticipating and adapting to further, future change.

Weather Center. The acceptability of the Szilagyi Waterspout Index for four extreme cases are computed and the availability of waterspout predictions have been examined in the study. In addition, a triangle diagram was created for the waterspout cases in the Antalya region for period of 2000 and 2012, which is composed of Sweat Index, relative humidity and 850mb wind speed. Key words: Climate Change, Extreme, Vortex, Waterspout, Szilagyi Waterspout Index, Triangle Diagram, Demre.

Exploring storminess on North Atlantic islands using reanalysis data

Author Aideen Foley

Affiliation Birkbeck, University of London

Storm events impact on the built and natural environment of North Atlantic islands, with a range of environmental, economic and social effects.

On the island of Orkney, for example, there are implications for the field of heritage conservation, with World Heritage sites such as the Neolithic settlement of Skara Brae at particular risk from increased erosion. Recent episodes of storminess in the UK invite speculation as to whether a shift is underway towards more extreme weather. However, the complex spatial dimensions of the regional storm climate necessitate more localised study.

Evaluation of Waterspouts by Szilagyi Waterspout Nomogram and Triangle Diagram

Author Sevinc A. Sirdas

Affiliation Istanbul Technical University

Co-authorsÖzmen, I., Yavuz, V.Y., Kaya, S. and Aydın, M

Climate change impacts on extreme and rare weather events are much more obvious so that many scientific studies have been focused on worldwide. The connection between the formation of waterspouts that are considered as rare event for Turkey and the climate change has been a matter of curiosity. The vortex incident and waterspout have been observed 260 times in the period between 1997 and 2015 at Turkey, and the most of them were observed in the coast and lakes of Antalya. In this study, the data sets of ground base stations and ERA- Interim are analysed for four extreme waterspout cases in Kale – Demre, Antalya station which were observed at the period between 2008–2013 were discussed in the study. ECMWF Reanalyse data ERA-Interim is used for different vertical heights, and the meteorological variables of ERA-Interim are downscaled on the station of Kale – Demre.

The vertical thermodynamic structure of vortexes are analysed by diagrams and vertical indexes of Plymouth State

The clearness index (KT) which is the ratio of the global solar radiation obtained at the surface to the total solar radiation at the top of the atmosphere was obtained. The diffuse fraction (KD) was obtained from the ratio of the diffuse solar radiation incident on the horizontal level of earth surface (HD) to the global solar radiation that incident on the surface level (H). The computed clearness index value were used to characterize the sky conditions into clear skies and overcast skies. Port Harcourt with low clearness index indicated low global solar radiation while Kano with large clearness index indicated high global solar radiation. The implications of these results on the effective utilization of solar energy are discussed. The results also serve as very useful for solar energy collectors in designing and estimation of solar application systems. Keywords: Clearness Index, Diffuse Fraction, Global Solar Radiation

Section 5


probability distributions and expected values, at single points (time extremes) and over areas (space-time-extremes).

In particular, the Tayfun nonlinear model is considered for the probability and expected value of maximum crest heights, while for the maximum crest-to-through wave heights expected values are estimated combining the Tayfun nonlinear model and the Quasi-Determinism theory.

For our purposes, we use the directional wave spectra produced by ERA-Interim over the entire global oceans, including marginal and enclosed seas (e.g., Mediterranean Sea), with 1°x1° spatial and 6-hour temporal resolutions. The spectral parameters provide parameters of the probability distributions and expected values of extreme waves.

An analysis of the directional spectrum parameters and extreme waves over the ERA-Interim reanalysed period (1979-2016) is conducted in order to: (i) highlight regions of the oceans that are more prone to the development of extreme waves, (ii) assess the presence of climatological trends in extreme waves, taken into account the 1991 discontinuity in significant wave height statistics due to the beginning of altimeter assimilation.

results were validated using root mean square (RMSE), accuracy and correlation coefficient, R.

The feedforward neural networks model of five inputs (latitude, longitude, elevation, month and year) had the best results with values of 0.86 and 6.68 for R and RMSE respectively. And given the accuracy of 93.32%, the networks can effectively be used to forecast for other locations in Nigeria. Tools such as neural networks that have the ability to understand the patterns in any given set of data are highly recommend for forecasting and studies of trends.

Global climate of extreme ocean waves from ERA-Interim

Author Francesco Barbariol

Affiliation ISMAR-CNR

Co-authorsA. Benetazzo (ISMAR-CNR, Italy), L. Cavaleri (ISMAR-CNR, Italy), M. Sclavo (ISMAR-CNR, Italy), JR. Bidlot (ECMWF, UK), P. Janssen (ECMWF, UK)

We present an application of the ERA-Interim dataset that we use for the global analysis of extreme ocean waves. The main goal is to assess, for the first time, the global signature of the multi-decadal climate of extreme waves. Features of extreme waves are here predicted in a probabilistic sense, i.e., the maximum crest and crest-to-through wave heights in a sea state are treated as random variables, of which we estimate the

able to reproduce the principal fire risk areas which are concentrated in the Sahelian region and in northern of South America from December to March, in subtropical Africa and Midwest region of Brazil from July to October.

In almost all continents the efficiency of the model was approximately 70% in presenting occurrences over 10 fires in the grid cell. The PFRI reproduces areas with high fire activity and those ones which present atmospheric patterns totally distinct from the equatorial zone, indicating that this index is an useful tool for forecasting fire occurrence worldwide because it is based on regionally vegetation and climate factors.

Forecasting Rainfall in Nigeria Using Neural Networks

Author Nsikan Obot

Affiliation University of Lagos

Co-authorsI. Humphrey (Department of Physics, University of Lagos)

Rainfall is about the most complex parameter in meteorological studies and if it is adequately forecasted, the problematic fallouts of excessive rain can be mitigated. From a total of fifty years data for twenty seven locations across Nigeria, forty years data were deployed in various artificial neural networks models to forecast for ten years of rainfall. The

Fire Susceptibilty under different atmospheric conditions

Author Alex Santos da Silva

Affiliation Federal University of Vicosa

Co-authorsF. Justino (Federal University of Vicosa), N. Leonardo (Federal University of Vicosa), V. Schumacher (Federal University of Vicosa), A. Comin (Federal University of Vicosa)

Based on Era-Interim Reanalysis and GPCP (Global Precipitation Climatology Project) datasets we analyzed the vulnerability to wildfire occurrence from 2001 to 2015. The investigation applies a Potential Fire Risk Index (PFRI) which runs a roughly exponential function adjusted for three atmospheric layers of the Haines Index (HI). The PFRI is set with eighteen classes of vegetation as boundary condition extracted from the International Geosphere and Biosphere Program.

This is formulated on the principle that the vegetation fire risk increases with the increasing duration of dry periods, type and natural cycle of vegetation phenology, maximum temperature and relative humidity of the air.

The daily global active fire from the Satellite Terra/MODIS was used to validate the analyses. It was demonstrated that under current climate and vegetation conditions the PFRI is

Section 5


maps are able to explain the atmospheric conditions at one to five days prior to the occurrence of the events in Indonesia, which has never been explored so far.

High resolution regional reanalysis: a tool for the identification of extreme wind surges in the German Bight

Author Natacha Fery


Co-authorsB. Tinz (DWD), A. Ganske (BSH), A. Andersson (DWD), L. Gates (DWD)

In the context of global climate change, interest in the study of very severe storm surges and their impacts on the southern North Sea and more particularly in the German Bight has increased over the last decades. In the framework of the research project EXTREMENESS, funded by the German Federal Ministry of Education and Research, two methods are implemented to identify extreme wind surges likely to cause significant damages along the coast of the German Bight.

To achieve this goal, high resolution reanalysis from the regional model COSMO-REA6 (Deutscher Wetterdienst, University of Bonn) is evaluated by means of recent and historic meteorological observations. A statistical wind surge model based on wind speed, wind direction and sea level pressure is optimized for extreme events that are detected in the dataset.

High Resolution Composite Maps for Extreme Rainfall in Indonesia

Author Heri Kuswanto

Affiliation Institut Teknologi Sepuluh Nopember (ITS)

Co-authorKiky Ferawati (Institut Teknologi Sepuluh Nopember-Indonesia)

Climate change has increased the intensity of extreme weather events in Indonesia. One of the strategies to minimize the risk is by developing a forecasting tool enable to provide an accurate prediction about the occurrence of extreme events. This research developed high resolution composite maps designed specifically for extreme rainfall events in Indonesia. High resolution refers to the grid space of the reanalysis dataset used to create the map. ERA-Interim reanalysis dataset has been chosen as the the input.

The composite maps provide information about the dynamic pattern of some weather variables in atmospheric (upper) levels as well as information about active zones associated to the events. Bootstrap resampling approcch has been applied to validate the map with certain degree of significant levels.

Some weather variables in the atmospheric levels show clear patterns to be used as a guidance to predict extreme rainfall events. The composite

Big Data of Earth Observation is split into parts individually processed, constantly updating the Earth view from space. Processed data will be publicly available for viewing, while thematic downloads will be charged. Potential customers are Environment NGO’s, local authorities, small and medium sized business in the forestry and agriculture domains, while cooperation with universities in imagery research projects is also envisaged. The collaboration with startup communities through preferential data access and accessible fees has the purpose of boosting further innovation and creativity.

Data will be processed using well-known algorithms for high resolution multispectral imagery (Sentinel2) and multiple instruments data (Sentinel 3). GREENTOP – Gamification of cRowdcomputing to ENhance EarTh Observation data Processing encourages internet users to support ESA’s initiative of distributing free spatial data.

Further applications include tacking input from IoT devices for enhancing analysis algorithms. This work is the object of a feasibility study financed by the European Union’s Horizon 2020 research and innovation programme – SME Instrument, under grant agreement No. 773660 and will be complete in October 2017.

GREENTOP – Gamification of cRowdcomputing to ENhance EarTh Observation data Processing

Author Sorin POP

Affiliation Indeco Soft

Co-authorsGabriel ZETE (Indeco Soft), Ana Maria POP (Indeco Soft), Ciprian GHIS,E (Indeco Soft)

The European Space Agency provides free access to great amounts of data from its space missions. Processing it for applications in forestry, land cover, land use, precision agriculture and other fields requires huge capabilities. Through gamification, a community of enthusiasts is encouraged to share their computing power to rapidly process small portions of imagery. Members can also participate actively in validating data manually, providing a human verification of the computer processed information.

User involvement, both for automated processing and manual validation will be encouraged through a gamification process (virtual badges, eCards, premium access to data, gifts of independent processing units – IoT devices). The Internet of Things, through small computing modules that process images using energy from renewable sources will organize an innovative mesh network of independent processing units providing green processing power.

Section 5


Inter-comparison of ERA-Interim, MERRA, NNRP reanalysis and GFS-ANL analysis data for Wind Resource Assessment across India

Author Chinmay Kulkarni

Affiliation Meteodyn

Co-authorEric Tromeur

Reanalysis data is extensively used in Wind Resource Assessment (WRA) to produce long-term correction series of measured wind data. A long-term correction series is necessary in order to reduce the uncertainties in the short-term wind observation data1. Good data is key to good WRA and to predict accurate wind energy production of a site.

The objective of the study is to compare the wind speed modelled by MERRA, ERAI, NNRP reanalysis and FNL analysis data sets with observations across 10 stations in India over the recent period of 2010-2016. The observation data is obtained from National Institute of Wind Energy (NIWE), India. The stations selected in the study are geographically well dispersed across India containing mixture of complex, urban and on-shore locations. These reanalysis data have different spatial and temporal resolution of grids.

In these shallow-groundwater systems, soil moisture of the unsaturated zone, and consequently the energy and water exchange with the atmosphere, is closely coupled to water table depth, which is thus a key variable that must be adequately modeled. We discuss the capability of an operational global land surface model to simulate peatland hydrology. Specifically, we evaluate the Catchment land surface model (CLSM) of the NASA Goddard Earth Observing System version 5 (GEOS-5) modeling and assimilation framework, which is one of the few global land surface models in which water table depth is modeled at all.

A preliminary analysis of groundwater levels from the GEOS-5 Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and other GEOS-5-based land-only products show very little differences between areas with peatlands and those with dominantly mineral soils. In contrast, observed water table levels show strong differences in temporal statistical moments between peatlands and areas with mineral soils. Therefore, we present an initial attempt to improve the GEOS-5 CLSM performance over peatlands by updating select parameters based on improved ancillary data and parameter optimization, while keeping the current GEOS-5 CLSM structure as used in MERRA-2.

Improving water level and soil moisture over peatlands in a global land modeling system

Author Michel Bechtold

Affiliation KU Leuven

Co-authorsG.J.M. De Lannoy (Department of Earth and Environmental Sciences, Belgium), D. Roose (KU Leuven, Department of Computer Science, Scientific Computing Research Group, Belgium), R.H. Reichle (NASA Goddard Space Flight Center, Global Modeling and Assimilation Office, Greenbelt, Maryland, USA), R.D. Koster (NASA Goddard Space Flight Center, Global Modeling and Assimilation Office, Greenbelt, Maryland, USA)

Peatlands are characterized by high soil moisture contents and hydrological dynamics that differ greatly from those in biomes on mineral soils. In combination with peatland-specific vegetation characteristics, this leads to distinct energy and water fluxes across the soil-vegetation-atmosphere interface over these environments. Covering 3% of the global land surface, peatlands can be a regionally dominant biome, and thus importantly influence the land surface boundary conditions for weather and climate simulations. However, modeling of peatland hydrology is a challenging task.

A second method consists of evaluating the so-called effective wind and its extremes. The effective wind is the result of the projection of the real wind onto that wind direction, for which the impact of the wind on the water level is most effective. The present study highlights the advantages of using these methods instead of the often used high percentile calculation for the identification of severe surges. The accuracy of the high resolution reanalysis is as also assessed for the storm conditions under consideration and climate projections are analyzed to provide a range of future severe wind surges.

Section 5


Data Relay (AMDAR) system and with the addition of a turbulence measure (the Global Aircraft Data Set, GADS).

Wind speeds and turbulence were obtained every 4 sec (~ 1 km spacing) at a fixed flight level (FL370, ~ 225 hPa). We examined the winter (DJF) North Atlantic jet stream region to study secular trends in wind speed and “light” turbulence. The observations were compared with reanalyses over a 12 year period, winter 2002-2013 (labeled by the January year), and a CMIP study of doubled CO2.

We have a sufficiently large dataset (3 billion total global observations, 500,000 for the North Atlantic per winter month) that we are able to subdivide the results into five longitude bands at ten degree intervals running from 60°W to 10°W and find quite coherent behavior along the North Atlantic jet. As would be expected, our results match the interannual reanalysis variations of the North Atlantic jet.

They are also consistent with conclusions of Delcambre et al. (2014) for doubled CO2: that the wind speed for the jet exit region shows a strengthening and the core shows a weakening. The trends in “light” turbulence are less clear, because the rarity of turbulence and the large interannual variability demands a longer data set to expose any secular trends. Our primary results are independent of computer models.

(floods) in the middle and lower reaches of the Yangtze River and the Yangtze-Huaihe valley but floods (droughts) in South China and North China.

On decadal scale, persistent floods in the middle and lower reaches of the Yangtze River but persistent droughts in South China and North China are mainly linked with weakening of VIMF by ASM and a dipole VIMF anomaly in the western North Pacific after the end of 1970s. In view of the in-phase relationship between summer rainfall anomalies and VIMF convergence anomalies in China, the analysed results also show interannual and decadal variations of VIMF by ASM can be better described by the ERA-40 reanalysis than the NCEP-R1 reanalysis.

Interannual variations and secular trends in winter North Atlantic jet stream wind speeds and turbulence from the GADS data set

Author Joel Tenenbaum

Affiliation SUNY Purchase

Co-authorsP. D. Williams (University of Reading, Reading, UK)

The North Atlantic jet stream is important for aviation, influencing flight routes, journey times, turbulence, and possible effects of climate change. This study used a dense set of aircraft observations relative to the Aircraft Meteorological

Interannual and Decadal Variations of Moisture Flux by Asian Summer Monsoon and Associated Rainfall Anomaly Patterns in China

Author Jilong CHEN

Affiliation Institute of Atmospheric Physics, Chinese Academy of Sciences

The NCEP/NCAR reanalysis data (NCEP-R1) and the ECMWF reanalysis data (ERA-40) for the period of 1958-2002 are used to estimate interannual and decadal variations of vertically integrated moisture flux (VIMF) by Asian summer monsoon (ASM) and investigate their association with summer rainfall anomalies based on monthly precipitation at 160 stations in China.

The results show that both VIMF by ASM and summer rainfall in China exhibit obvious biennial rhythms as revealed by time coefficient of the leading EOF mode. When summer VIMF is strong (weak) in the south Asia monsoon region, a dipole VIMF anomaly in the East Asia – western North Pacific is propitious to negative (positive) VIMF convergence anomalies in the middle and lower reaches of the Yangtze River and the Yangtze-Huaihe valley but positive (negative) VIMF convergence anomalies in South China and North China, which result in a meridional tripole structure of rainfall anomalies in eastern China, i.e., droughts

The gridded reanalysis data therefore is interpolated at the station location using inverse distance weighted (IDW) average technique2 for comparison with observation. Indian continent gets high wind during south-west monsoon, a period of four months from June to September. The monthly mean wind speed profiles of reanalysis data have shown good agreement with observations and with each other.

It is found that, all reanalysis monthly mean values under-estimate the observation values for most of the cases though they catch the trend successfully. The reanalysis data also captured the prevailing south-west wind direction of observation successfully. However, the reanalysis data sets failed to frame the correct diurnal variation as per observation for some stations.

Overall, the statistical analysis of RMSE, MAE and BIAS of MERRA, ERAI, NNRP and FNL shows small variations with observations. However, ERAI reanalysis performed better than other reanalysis data, even if the selection of reanalysis data for WRA still depends on the location of site.

Section 5


and a modelled value for the melt water production. The evaluation of different melt variables reveals that different years will be identified as years of extreme melt depending on how melt is quantified.

Our study includes a comparison between the ice surface temperature of the MODIS product and ERA-Interim surface temperature. ERA-Interim’s surface temperature is found to be mostly warmer than MODIS IST. However, the difference in the temperatures is smaller when the temperatures are close to the melting point.

We study the weather conditions in March-May and June-August separately to understand which kind of atmospheric conditions occurred in the early stage of the melt season, as well as during the strongest melt. Our interest is especially in the surface temperature, near surface wind, total cloud water content and atmospheric pressure. The meteorological variables are retrieved from ERA-Interim and NCEP-CFSR reanalyses.

forecasting system in several points in the Persian are compared and the reason of differences are investigated.

Number of melt days and atmospheric conditions in Greenland in 2000-2014

Author Ilona Välisuo


Co-authorsT. Vihma (Finnish Meteorological Institute), R. Pirazzini (Finnish Meteorological Institute), M. Schäfer (Finnish Meteorological Institute)

Surface melt on Greenland ice sheet and extremely warm temperatures in the Arctic since 2007 have been linked to negative North Atlantic Oscillation (NAO) in numerous studies. Cases of extreme melt on Greenland are also related to anticyclonic circulation centered over Greenland, which favours warm-air advection to Greenland.

We investigate the connections between interannual variations of the number of melt days on Greenland ice sheet and atmospheric and surface conditions in 2000-2014. We calculate the number of melt days using a MODIS based product on ice surface temperature. As the spatial coverage of the MODIS product is limited, we complement it with ERA-Interim surface temperature. To quantify melt, we use also satellite based maximum and cumulative melt extent,

Finally, the spatial structure of the four weather regimes has been related to the four main monthly teleconnection patterns in the Euro-Atlantic region (NAO, EA, EA/WRUS and SCAND) obtained from the same reanalysis. Results confirm the usefulness of the monthly classification for the characterisation of the monthly wind speed variability over most part of Europe.

Marine Forecasting Systems in Caspian Sea, Persian Gulf and Oman Sea

Author Alireza Vaselali

Affiliation Behin Tarhe Appadana (BETA Group)

Co-authorsAliasghar Golshani (Met Ocean Expert, Beta Group Consulting Engineers), Said Mazaheri (Research Assistant Professor, Iranian National Institute for Oceanography and Atmospheric Science)

There are several global marine forecast systems based on large scale regional data covering Iranian seas which are freely available on their websites. They are also several local marine forecast systems in Iranian waters. This paper performs an inter-comparison among different marine forecasting systems in Iranian seas in order to evaluate the accuracy and difference between them and give a proper ground for further investigation and research in this crucial issue. For this purpose, the results of two

Intercomparison of monthly Euro-Atlantic weather regimes obtained from different reanalysis and of their influence on wind energy resources

Author Nicola Cortesi

Affiliation Barcelona Supercomputing Center (BSC)

Co-authorsNube González-Reviriego, Veronica Torralba, Albert Soret, Francisco Javier Doblas-Reyes

For wind energy companies, it is crucial to identify the main sources of wind speed variability affecting their wind farms, at all time scales. It is known that changes in the frequencies of occurrence of the monthly Euro-Atlantic weather regimes determine most of the variation of wind speed anomalies over Europe (Hannachi et al., 2017).

Firstly, the impact of the monthly frequency of the four main monthly weather regimes on 10-m wind speed variability over Europe has been evaluated. Subsequently, an intercomparison of the spatial patterns and frequencies of the monthly weather regimes derived from daily sea level pressure data during last 35 years has been performed for three different reanalyses: JRA-55, ERA-Interim and NCEP/NCAR.

Section 5


challenge for users to download what they need. For example, extracting one parameter at a single point for 30 years may take over 15 hours. Moreover, users wish to have such a long time series in a single file.

The GES DISC is exploring methods for the improvement of accessing big model data. One approach attempts to optimize file structure. Initial performance tests of year-file of hourly data have shown dramatic improvement of the accessibility.

Reanalyses.org: Advancing user and producer needs for reanalysis with services and tools

Author Catherine A. Smith

Affiliation NOAA/ESRL PSD & CU CIRES

Co-authorsG.P. Compo (NOAA/ESRL PSD and CU CIRES)

The University of Colorado/CIRES and NOAA/ESRL Physical Sciences Division host two types of support for users and producers of reanalysis datasets. The first is the website “Reanalyses.org”. Using a collaborative Wiki framework, the goal of reanalyses.org is to facilitate comparison between reanalysis and observational datasets.

The data support team at GES DISC, working closely with the MERRA-2 science team, has created value added data tools and provided high quality services to the broad user community. MERRA-2 subsetter is a powerful data tool for downloading selected parameters, region, and time.

One function is, with a number of interpolation methods, to regrid the spatial resolution to models, such as ERA, cfsr, GEOS, GLDAS, etc., and to save the data in a different format. In addition, the interoperable services, such as OPeNDAP and GDS are provided for remote accessing data via using applications such as Matlab, GrADS, R, IDV, etc. Selected MERRA-2 parameters have been integrated into Giovanni, an online visualization and analysis system developed in-house at GES DISC.

Giovanni has more than twenty visualization functions that enables easy and quick exploration of data by performing basic statistical analysis and comparisons between variables. For example, it generates maps with user defined time range and is able to adjust the color scales for best showing interested signals. It generates time series for a single point, an area, a political boundary, such as countries, or a water shed.

Application research studies concerning renewable energy, extreme weather, and air quality, etc. require long-term data at high temporal resolutions. With native file structure of the hourly data, it is a

Our assessment of the influence of forcing inaccuracies on the simulated Antarctic sea ice allows disentangling the model biases that can be reduced thanks to better atmospheric forcings from those that would require improvements of the physics of the ice or ocean model.

Online Visualization and Value Added Services of MERRA-2 Data at GES DISC

Author Suhung Shen

Affiliation George Mason University & GES DISC NASA

Co-authorsDana M. Ostrenga (ADNET and NASA), Bruce E. Vollmer (NASA), Mahabaleshwa S. Hegde (ADNET and NASA), Jennifer C. Wei (ADNET and NASA), Michael G. Bosilovich (NASA)

NASA climate reanalysis dataset from MERRA-2, distributed at Goddard Earth Sciences Data and Information Services Center (GES DISC), contains numerous data for atmosphere, land, and ocean, that are grouped into 94 products of archived volume over 333 TB. The data files are saved as day-file and month-file for hourly and monthly time interval respectively.

Each product contains parameter numbers varying from 2 to 125. Due to the large number of products, data files, and data volumes, it is a challenge for users to find and download the only parameters and spatial region of interest.

On the sensitivity of Antarctic sea ice model biases to atmospheric forcing uncertainties

Author Antoine Barthélemy

Affiliation Université catholique de Louvain

Co-authors

Hugues Goosse (Université catholique de Louvain), Thierry Fichefet (Université catholique de Louvain), Olivier Lecomte (Université catholique de Louvain)

Although atmospheric reanalyses are an extremely valuable tool to study the climate of polar regions, they suffer from large uncertainties in these data-poor areas. In this work, we examine how Antarctic sea ice biases in an ocean-sea ice model are related to these forcing uncertainties.

Three experiments are conducted in which the NEMO-LIM model is forced by different atmospheric forcing sets. The minimum ice extent, the ice drift and the ice thickness are sensitive to the reanalysis chosen to drive the model, while the wintertime ice extent and inner pack concentrations are barely affected.

The analysis of sea ice concentration budgets allows identifying the processes leading to differences between the experiments, and also indicates that large and similar errors compared to observations are present in all three cases.

Section 5


Risk and vulnerability analysis in Madagascar using AHP method

Author Tsiory Rakotoarison

Affiliation EMIT University of Fianarantsoa

Co-authorsAimé Richard Hajalalaina (Ecole de Management et d’Innovation Technologique, Université de Fianarantsoa, Madagascar)

The major hazards, namely cyclone, flood and drought, occur frequently and periodically in Madagascar. These extreme phenomena cause direct mortality, flooding, damage to infrastructure such as roads, schools, health centers and population centers, as well as crop destruction and landslides. Disasters hamper development programs and result in loss of people’s property that leads to a decline in the economic level. Risk and vulnerability analysis is a necessary part of decision-making on risk and disaster management. In addition, spatial decision-making problems are multicriteria nature. For this purpose, the multicriteria hierarchical analysis (AHP) method was applied to ERA-Interim reanalysis data from ECMWF coupled with cyclonic data and socio-economic data, in order to break down the complex problem into a structure Hierarchical analysis for risk analysis and vulnerability to major hazards in Madagascar.

numbers and Accumulated Cyclone Energy (ACE) over the 135-year period from 1878 to 2012.

We find that these fields replicate historical hurricane activity surprisingly well, showing that contemporary statistical models and their seasonal physical links have long-term robustness. We find that August-September zonal trade wind speed over the Caribbean Sea and the tropical North Atlantic is the environmental field which individually replicates long-term hurricane activity the best, and that trade wind speed combined with the difference in sea surface temperature between the tropical Atlantic and the tropical mean is the best multi-predictor model.

Comparing the performance of the best single-predictor and best multi-predictor models shows that they exhibit little difference in hindcast skill for predicting long-term ACE but that the best multi-predictor model offers improved skill for predicting long-term hurricane numbers. We examine whether replicated real-time prediction skill 1983-2012 increases as the model training period lengthens and find evidence that this happens slowly.

We identify a dropout in hurricane replication centered on the 1940s and show that this is likely due to a decrease in data quality which affects all data sets but Atlantic sea surface temperatures in particular. Finally we offer insights on the implications of our findings for seasonal hurricane prediction.

available. A full set of statistics is output. The 3rd tool, WRIT Distributions, can be used to examine the distributions of daily data from several reanalysis and observed datasets.

Users can compare distributions to each other and to a set of provided distributions. The 4th tool, WRIT Trajectory, allows users to plot atmospheric trajectories from several reanalysis datasets using 4x-times daily pressure level data to calculate the path of tracer particles.

Replicating Annual North Atlantic Hurricane Activity 1878-2012 from Environmental Variables

Author Philip Klotzbach

Affiliation Colorado State University

Co-authorsMark Saunders (Mullard Space Science Laboratory, University College-London)Adam Lea (Mullard Space Science Center, University College-London)

Statistical models can replicate annual North Atlantic hurricane activity from large-scale environmental field data for August and September, the months of peak hurricane activity. We assess how well the six environmental fields used most often in contemporary statistical modeling of seasonal hurricane activity replicate North Atlantic hurricane

To accomplish this, reanalyses.org is divided into reanalysis types: Atmosphere and Ocean (with Land to come). Each type includes webpages that describe the datasets, provide references, help users obtain the data, directs users to plotting and analysis tools for the data, and provides a place for researchers to describe their research using the reanalyses.

Pages can be edited by validated users. Anyone can post a comment on most pages with experts available to answer questions. The pages are searchable and indexed. There are even “private” areas for groups such as the WCRP Task Team for the Intercomparison of ReAnalyses (TIRA) to collaborate. To the Tools area of Reanalyses.org, CIRES and PS have contributed the “WRIT” or Web-based Reanalysis Intercomparison tools at https://www.esrl.noaa.gov/psd/data/writ/.

There are currently four tools available. In the Writ Maps Tool, one can plot maps and cross-sections from monthly-mean fields of reanalysis datasets. One can also plot the difference of any two datasets. Users can examine means, anomalies, or climatologies using different seasons and sets of years. Some other observational datasets are provided for comparison. The 2nd tool, WRIT Timeseries, allows users to plot similar datasets but instead compare gridpoint or area-averaged time-series. Users can plot and/or compare time-series, specifying the region or season. Land/ocean masking functionality is

Section 5


Southern hemisphere low-frequency troposheric circulation components and their contribution to river runoffs changes in Central Eastern Patagonia

Author Eduardo A. Agosta

Affiliation UCA/CONICET/FCAGLP

Co-authorsR.A. Maenza (Grupo de Geología de Costas y Paleoecología, Instituto de Investigaciones Marinas y Costeras (IIMYC-UNMDP-CONICET)), D.C. Araneo (Facultad de Ciencias Exactas y Naturales (FCEN), Universidad Nacional de Cuyo (UNCuyo), CONICET).

Patagonia is under influence of the westerlies that drive the amount and distribution of precipitation in the Southern Hemisphere (SH) middle latitudes. Two sub regions with highly distinct precipitation features are: wet Western Patagonia, from the Pacific coast to the Andean highs; and dry Eastern Patagonia, leeward the Andes in the Argentine steppe plateau towards the Atlantic.

The cold season (Apr-Sep) is the rainy season over the mountains in central Patagonia (40°S-50°S), leading to snow accumulation over river catchment areas. The winter snow feeds river runoffs to the east in EP. The Tecka-Gualjaina (TG) River is one of those which drain their streamflow into the South Atlantic, from

throughout of ASEAN and a part of Pacific. There are 3 step methods of SA-OBS, one of the method is an interpolation of monthly mean/total using thin plate splin to define the spatial trend, daily anomalies using global kriging with a single variogram for all days.

Climate information and monitoring product of SA-OBS are daily maps for 4 elements TN, TX, TG and RR closely of the ASEAN and Pacific region. Benefits of the SACA&D gridding data is the monitoring extreme events in the region when La Nina and El Niño year and its impact like as drough, flood, forest fire. In the National level, BMKG has developed the climate data online services included gridding data and Indonesia has implemented the data policy by WMO resolutions 60 and followed by Goverment regulation that the cimate data is free charge for public.

to complete the data. Quality control data in SACA&D is using homogeinity test from Wijngard to clasify the data is usefull, doubfull and suspect. The other methods are called blending and non blending to extend the period of climate data.

Meta information for the daily series is provided methode both for the blanded and non blended series. The blended series have been tested for homogeneity, which is relevant to assess the quality of each series for climate change information. To get the climate monitoring and information services in the ASEAN and Pacific region, there are available in 44 indices included trends, changing probabilities of high impact extremes like as droughts, floods, health risk, inparticularly of food security, energy, transportation and others. Indice extremes are available in form of time series plot, trend maps, anomaly map index, climatology maps for this region.

Data Gridding of the SACA&D developed between KNMI Holland and BMKG to increase the Climate monitoring and information services namely SA-OBS Version1.0 and It had used effectively in 2016 until now. SA-OBS made with regular grid 0.25o and 0.50o With coverage area all ASEAN country between 25o North to 25o South and from 80o East to 180o East and available in NetCDF format. SA-OBS consist of 4 parameters of daily value for TX, TG, TN and RR with period data from 01 January 1980 to 31 Dec 2014. Station density of this RR is 5979 series observations

SACA&D gridding data as a tool for climate monitoring and information services for the Asean and Pacific Region

Author Sunaryo Naryo

Affiliation BMKG Indonesia

SACA&D is a Website visualisation of the climate dataset for the ASEAN and Pacific region.

SACA&D is a part of ICA&D (International Climate Assessment and Dataset) network which is consist of WACA&D (West Africa), LACA&D (Latin America), SACA&D (Asean and Pacific) and ECA&D (Eropean) to get access of SACA&D website is http://sacad.database.bmkg.go.id. Agency of Meteorology, Climatology and Geophysics of Indonesia Jakarta (BMKG) has managing this Website and it has launched in the event of the Second International Workshop of SACA&D on April 2012 in Bogor Indonesia. SACA&D plays an important role in climate information and monitoring in the region especially for the ASEAN and pacific region. It’s built of the cooperation between BMKG Indonesia and KNMI Holland in supported by 10 ASEAN member countries, and 6 others countries in the Pacific region included of Australia. All 16 countries has contributes a climate daily observation data with 10 parameters and synoptic data which is GTS exchanges data every 3 hourly and other source data from GHCN and ECMWF data model as a comparison and

Section 5


fractal dimension indicates the property of self-similarity, and in the case of this study, wherein it is applied to the temporal behaviour of rainfall at a fine (10-minute) resolution from a total of 44 observatories, it provides insights into its more or less convective nature.

The methodology of Jenkinson & Collison which automatically classifies synoptic situations at the surface, as well as an adaptation of this methodology at 500 hPa, were applied in order to gain insights into the synoptic implications of extreme values of the fractal dimension. The highest fractal dimension values in the study area were observed in places with precipitation that is more random over time with generally high totals.

Four different regions in which the atmospheric mechanisms giving rise to precipitation at the surface differ from the corresponding above-ground mechanisms have been identified in the study area based on the fractal dimension. In the north of the Iberian Peninsula, high fractal dimension values are linked to a lower frequency of anticyclonic situations, whereas the opposite occurs in the central region.

In the Mediterranean, higher fractal dimension values are associated with a higher frequency of the anticyclonic type and a lower frequency of the advective type from the east. In the south, lower fractal dimension values indicate higher frequency with respect to the anticyclonic type from the east and lower frequency with respect to the cyclonic type.

However, due to the availability of radar data, COSMO-REA2 only covers the period from 2007-2013. In our downscaling approach, we use the analog ensemble technique to generate synthetic time series of 2D precipitation fields for earlier time periods. Here, we use the 20-year (1995-2014) data set COSMO-REA6 at 6km resolution as predictor.

The probabilistic estimates for the precipitation are created by finding analogs in the existing COSMO-REA2 data set for each time step in the reconstruction period (1995-2006). The analogs are determined as the N best matches in terms of a metric calculated using COSMO-REA6. These analog ensembles are then validated against independent observations over central Europe.

Synoptic implications at sea level pressure and 500 hPa of the temporal fractality of precipitation according to the ERA-Interim reanalysis products

Author Oliver Meseguer-Ruiz

Affiliation Universidad de Tarapacá

Co-authorP. Sarricolea (Departamento de Geografía, Universidad de Chile)

Precipitation on the Spanish mainland and in the Balearic archipelago exhibits a high degree of spatial and temporal variability, regardless of the temporal resolution of the data considered. The

SST anomalies, show significant slow components consistent with the trend and changes in the TG streamflow. Trends in tropospheric fields during the river peak season are present even if inhomogeneities are removed.

Statistical Downscaling of 2D Reanalysis Fields with the Analog Ensemble

Author Jan D. Keller

Affiliation Hans-Ertel-Centre for Weather Research

Co-authorsL. Delle Monache (National Center for Atmospheric Research, Boulder, USA), S. Alessandrini (National Center for Atmospheric Research, Boulder, USA)

Reanalyses provide a valuable source of information on meteorological parameters as retrospective time series. In order to exploit these data, a statistical downscaling approach can be applied. Such an approach acts as a correction of systematic errors in the reanalysis with respect to the parameter (predictand) in consideration. Reanalysis intercomparison has shown the value of using very high model resolution combined with the assimilation of radar data with respect to the representation of precipitation in the regional reanalysis COSMO-REA2 at 2km horizontal resolution (Wahl et al. 2017).

the Andes to the Atlantic. We explored the influence of tropospheric circulation and sea surface temperature (SST) anomalies on the interannual-to-decadal streamflow variations of the TG River for the season of maximum streamflow (Jun-Nov) and the season of minimum streamflow (Dec-May). The maxima show negative trend along records. There is a change in the streamflow anomalies by the early 1980s, evolving from a positive predominance before to a negative one after.

The minima show stationarity (no trend). The intra-decadal quasi-cycles are dominant in both seasonal streamflow maxima and minima. Teleconnections related to the streamflow were analyzed using ERA-Interim, NCEP/NCAR I, 20C, and ERA-20C reanalysis datasets and other oceanic and atmospheric global datasets. Detrended streamflow maxima are linked to a quasi-stationary Rossby wave (QSW).

Tropospheric circulation anomalies, symmetric about the equator, are possibly associated with tropical convection, induced by anomalous SST in the equatorial western Pacific. The QSW affects the position and intensity of the subtropical and polar jets, altering winter precipitating transient perturbations. Detrended streamflow minima are linked to a high latitude annular mode-like variability, modulated by a mid-latitude wave-3 structures over the Pacific and Atlantic. Trend analysis and inhomogeneity tests on SH tropospheric circulation fields and

Section 5


means and 12 month running means. The post for each month includes a short discussion about the salient points relevant to that month and ECV.

The list of ECVs considered, to date, is surface air temperature, sea-ice, precipitation, surface humidity and soil moisture. This presentation will show some of the recent highlights from this climate monitoring, including the record high global surface air temperatures experienced during 2015 and 2016 and illustrated by ERA-Interim.

The Mediterranean Climate Modes: their seasonal variability, impacts and predictability from renalysed fields.

Author OrtizBeviá Maria J.

Affiliation University of Alcala

Co-authorsRuizde Elvira A. (University of Alcalá), Alvarez-García F. J. (University of Alcalá)

The Mediterranean region variability is characterised by several regional Climate Modes. Some among these, as the Western and Central Mediterranean Mode (WMM) or the Mediterrenean Dipole Mode (MDM), are characterised from indexes obtained from the Mediterranean SST anomalies. Others, as the Mediterranean Oscillation (MO) or the Western Mediterranean Oscillation (WMO), are monitored from indexes obtained from atmospheric (SLP) fields.

In this work we are interested in the numerical modeling of marine currents, which allows us to describe their direction and speed on the studied area. Our contribution to this work was made using the SWAN digital model. The characteristics obtained will be presented in the form of maps or tables of values.

The contribution of reanalysis to climate monitoring

Author Berrisford Paul

Affiliation ECMWF & NCAS Climate

Co-authorsD. Dee (ECMWF), H Hersbach (ECMWF), J. Munoz-Sabater (ECMWF), E. Remete (ECMWF), I. Rozum (ECMWF), A. Simmons (ECMWF), J-N Thepaut (ECMWF)

The Copernicus Climate Change Service (C3S) includes in its product portfolio, reanalyses and a climate monitoring facility. These two products are being used to monitor the climate by providing monthly updates on the climate for several ECVs. The monthly updates are posted onto the Copernicus website within a few days of the end of each month. Currently, the main sources of content are the ERA-Interim and ERA5 global reanalyses.

The content varies depending on the ECV, but typically includes global and European maps of anomalies for the month and the last year and global and European time series for monthly

information sector and science users. This presentation will give an overview and demonstration of this online monitoring tool.

The characterisation of the marine renewable energy resource (currents energy), on a Moroccan coastal zone using SWAN model

Author Hazim Salma

Affiliation Mohamed V University/IRESEN

Co-authorsHazim Salma (1,2), Benazzouz Aissa (3), Ghuennioui Abdellatif (2), El Ouatouati Ahmed (1), Taha Janan Mourad (1), Naimi Zakaria (2), Badr Ikken (2). 1: Mohamed V University, 2: Institut de Recherche en Energie Solaire et Energies Nouvelles (IRESEN) 3:Institut supérieur d’études maritimes ISEM

Due to its geographical position, Morocco has a great renewable energy resources potential, especially the Marine Renewable Energy (MRE/EMR). It has 2 seas: Mediterranean and Atlantic seas, this last one is characterized by its predictability and potential that is not exploited yet. The aim of this work is the characterisation of the marine renewable energy resource, more precisely the marine currents, on a Moroccan coastal zone; the Terfaya zone, with a spatial resolution of 200m.

The C3S Climate Monitoring Facility

Author Iryna Rozum

Affiliation ECMWF

Co-authorHans Hersbach (ECMWF)

On behalf of the European Commission, ECMWF operates the Copernicus Climate Change Service (C3S). C3S combines climate observations with the latest science to develop comprehensive, quality-assured information about the past, present and future state of the Earth’s climate. As part of this service a web-based tool is developed that allows users to interactively browse, visualise, analyse and compare time series for essential climate variables (ECVs) from various sources as they become available in the C3S Climate Data Store (CDS).

This includes ECVs directly obtained from satellite data (such as from ESA’s Climate Change Initiative, and operational products from C3S providers) and reanalysis (such as ERA-Interim and ERA5). An associated event data base displays relevant metadata to assist users to correctly interpret and understand results (including natural events such as volcanic eruptions and data events such as changes in the global observing system).

The CMF will form an integral part of the CDS toolbox and will serve a wide range of users including the sectorial

Section 5


Subtropical High (NPSH) over East Asia by about 5-70 of longitudes.

While the west Indian Ocean SSTs appear to be related with summer monsoon rainfall over northern parts of India and North China, and may be instrumental in the decreasing trend in the summer monsoon rainfall over northern parts of India and over North China, SSTs over the West Pacific Ocean (WPO) appear to be related with summer monsoon rainfall over southern parts of India and over South Korea-Japan sector.

Thus the increasing trends over these regions may be related with SSTs over the WPO. Outputs from the Coupled Model Inter-comparison Project Phase 5 (CMIP5) are investigated using historical simulations (1861-2005) and future projections (2005-2100) under the RCP4.5 scenario. In spite of large spread among the CMIP5 models, future projections in the summer monsoon rainfall over South as well as East Asia indicate a multi-decadal variability, displaying certain epochs of more rainfall over South Asia than over East Asia and vice versa.

Tele-connections between the South and East Asian monsoon rainfall also exhibits a multi-decadal variability with alternate epochs of strengthening and weakening relationship. Furthermore large-scale circulation features such as the monsoon trough over South Asia and the NPSH depict an oscillatory behavior with east-west-east shifts, probably suggesting that the recent trends may be a part of natural climate variability

Trends and Tele-connections among South and East Asian Monsoons: Evidences through NCEP-NCAR and CMIP5 Data

Author Ramesh Kripalani

Affiliation Indian Institute of Tropical Meteorology

Co-authorsM. Mujumdar (Indian Institute of Tropical Meteorology), A.Prabhu (Indian Institute of Tropical Eteorology)

Recent trends and tele-connections in the summer monsoon rainfall over South and East Asia are examined for the observational period 1970-2014. Trend analysis indicates that over South Asia one contiguous region over northern part India exhibits a significant decreasing trend and another region over the southern part of India exhibits a significant increasing trend in the summer (June through September) monsoon rainfall.

However over East Asia two regions one over the Korea-Japan peninsula and another over South China indicate a significant increasing trend. Incidentally, the summer monsoon rainfall over North China also indicates a decreasing trend. Furthermore analysis of SSTs, MSLP and winds at lower troposphere indicates that the entire monsoon flow appears to have shifted westwards, with the low pressure monsoon trough over South Asia by 2-30 of longitudes and the North Pacific

To represent the zonal mean fields, the mass-weighted isentropic zonal mean (MIM) Method (Iwasaki 1989) is applied to JRA-55. The MIM method is suitable for the examination of zonal momentum budget, and enables analysis of a single hemispheric cell, such as Blewer-Dobson circulation in the stratosphere and the extra-tropospheric direct circulation.

In order to extract variability synchronized with BSISO or lower (higher) frequent variability than BSISO, temporal filtering based on Duchon (1979) is also carried out to the zonal mean fields obtained by the application of the MIM method. We found some characteristic features of the zonal wind field during the significant BSISO: Hemispherically symmetric westerly anomalies are observed from mid-troposphere up to the tropical tropopause layer (TTL) just after the northward migration of active convective region in BSISO region, and move poleward in both hemispheres in spite of meridional asymmetry of the convective activity: In the extra-tropical upper stratosphere of the Northern Hemisphere, both easterly anomalies and positive potential temperature anomalies are statistically significant during the northward migration of active convective region.

Moreover, our results also reveal that the amplitude of BSISO is extraordinarily large during the strong low-frequency easterly anomalies at around the 20 hPa level associated with quasi-biennial oscillation (QBO) and suggest influence of the stratospheric circulation on the activity of BSISO in the troposphere.

In the work to be presented we compare the characteristics of these modes obtained from different Reanalysed fields (ERA-40, Had ISST2 in one case NCEP, ERA-40 and ERA-20C in the other also compare their impacts on the precipitation and the temperature fields of the neighbouring regions (CRU and U Delaware reanalysis). We also identify potential predictability fron the seasonal teleconnections of these modes with the midlatitudes or tropical variability.

The Relationship between Boreal summer Intra-seasonal Oscillation and the Stratospheric Circulation

Author Yayoi Harada

Affiliation Meteorological Research Institute/Japan meteorological Agency

Boreal summer intra-seasonal oscillation (BSISO) is a phenomenon that active convective region migrate northward in the Indian Ocean and the western Pacific with a period of 30 – 90 days. In this study, statistical relationships between BSISO and the stratospheric circulation are examined focusing on the variabilities of the zonal wind fields both in the troposphere and stratosphere. BSISO index based on Kikuchi et al. (2012) and the Japanese 55-year Reanalysis (JRA-55, Kobayashi et al. 2015) are used for composite analysis.

Section 5


The high resolution reanalyses COSMO-REA6 (6 km horizontal resolution, 40 vertical layers) and COSMO-REA2 (2 km horizontal resolution, 50 vertical layers) are based on the operational numerical weather prediction model COSMO. REA6 covers Europe and the Mediterranean region (CORDEX EUR-11 domain), REA2 is limited to Germany and its neighboring regions.

The coarser reanalysis is available for two decades from 1995 to 2014 and the finer from 2007 to 2013. Both reanalyses are generated with a nudging scheme to assimilate observations. In this quality assessment, independent observations of global radiation provided by the Baseline Surface Radiation Network (BSRN) are used. For wind speed evaluation 10m above ground SYNOP observations serve as verifying “truth”. Vertical wind profiles are compared to measurements from two meteorological masts in Jülich and Hamburg (Germany).

The evaluation shows that while the regional reanalyses have some deficiencies, they show significant improvements for radiation and wind speed scale dependent correlations compared to global reanalyses such as ERA-Interim.

Andreas Hense (Meteorological Institute, University Bonn, Germany), Susanne Crewell (Institute of Geophysics and Meteorology, University of Cologne, Germany)

The ongoing energy transition causes major challenges for many stakeholders due to the spatiotemporal inhomogeneity of renewable energy sources: (1) The transition system operator is challenged to ensure the balancing between energy supply and energy demand. (2) The distribution system operator is challenged to provide the required infra structure from centralized to de-centralized electricity generators. (3) The spot market participants are challenged by dealing with volatile energy supplies. In order to overcome these problems it is crucial to know where, when and to what extent renewable energy can be generated.

Atmospheric reanalyses offers interesting opportunities for a posteriori studies, since they provide all relevant meteorological quantities in a gridded and consistent way. Especially, high-resolution reanalyses with gird sizes of a few kilometers allow detailed studies on small scale variability. Therefore, we provide an evaluation of regional reanalyses with respect to renewable energy related quantities such as wind speed and solar energy.

This work focuses on two high resolution reanalyses developed within the Hans-Ertel Centre for Weather Research of the German Weather Service (DWD).

We will carry out spatial and temporal analyses, as well as inter-variable correlation analyses of ERA5 data compared to NCEP/NCAR during harmattan season over West Africa for multiple harmattan-related variables (relative humidity of air near the surface, wind velocity and the difference between daily minimum and maximum near-surface temperature). For variables affecting cocoa crops all throughout the year, like temperature, soil humidity and precipitation, analyses will span the full time series and, in the case of precipitation, other, gauge and satellite-based data sets will be considered for comparison.

Validation of COSMO-REA6/2 in respect to renewable energy applications

Author Christopher Frank

Affiliation Hans-Ertel-Centre for Weather Research & University of Cologne

Co-authorsSabrina Wahl ((Hans-Ertel-Centre for Weather Research, Climate Monitoring and Diagnostics, Germany), (Meteorological Institute, University Bonn, Germany)), Jan D. Keller ((Hans-Ertel-Centre for Weather Research, Climate Monitoring and Diagnostics, Germany), (Deutscher Wetterdienst, Offenbach, Germany)), Bernhard Pospichal (Institute of Geophysics and Meteorology, University of Cologne, Germany),

Use of reanalyses in climate monitoring and research for the cocoa industry

Author Alina Gainusa-Bogdan

Affiliation Rockwinds

Co-authorA. Diedhiou (National Research Institute for Sustainable Development (IRD), France)

Providing gridded, global coverage over long, uninterrupted periods of time for a wide array of variables with physically-consistent fields, reanalyses are an extremely valuable source of data for operational climate monitoring and applied research for the agricultural sector. The cocoa trading company Rockwinds has been using the NCEP/NCAR reanalysis to monitor and gain new insights into the development of the harmattan over West African cocoa regions over the last three harmattan seasons in order to better predict the subsequent evolution of African cocoa crops.

Besides numerous merits, the NCEP/NCAR operational product also has some drawbacks, one of the most obvious ones being its coarse spatial resolution, of major concern for analyses targeting the relatively narrow African cocoa belt. It is thus with great interest that the release of several years of the new, high-resolution ERA5 data is expected in June 2017.

Section 5


statistically characterize the resource in specific sites, therefore the use of high-resolution wave models is mandatory.

Wave models of third generation are based on the evolution of the two-dimensional wave spectrum, defined in each grid point of the model, that is function of wave frequency and direction. Waves are forced by surface wind stress and, in open boundary regions, depend also on the propagation of waves originated from outside the region.

In this case, in order to perform wave simulations, besides surface forcing represented by wind components, the entire spectra of incoming waves along the boundaries are needed. In this work we present a very high-resolution wave resource assessment in a region of the Mediterranean Sea, forced at the surface and laterally by ERA-Interim reanalysis. The 10-year simulation has been performed using SWAN (Simulating Wave Nearshore) model.

In this work, we describe the six-week climate outlooks developed and tested in the CLIPS project during the summer season 2017 and show the first verification results.

Wave resource assessment for the development of wave energy sector

Author Gianmaria Sannino

Affiliation ENEA

Co-authorsA. Carillo (ENEA), M.V. Struglia (ENEA)

The growing interest in the Blue Energy sector represents an opportunity for the sustainable growth of maritime economies, the sustainable development of marine areas and the sustainable use of marine resources. Among them the wave energy sector can play an important role in the clean energy economy, as it is very abundant, diffuse and renewable.

Its exploitation is based both on technological research aimed to the development of new efficient devices, and on the accurate assessment of the resource. In this view, a complete statistical characterisation of waves is essential both to optimize the design of the wave energy converter devices and to estimate in advance the productivity of a site. Available observations, either buoys or satellites, are inadequate to

Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800) Keywords Drought Characteristics, Reference Period, SPEI

Verification of six-week forecasts in Finland with reanalysis data

Author Natalia Korhonen


Co-authorsO. Hyvärinen (Finnish Meteorological Institute), T.K. Laurila (Finnish Meteorological Institute), A. Vajda (Finnish Meteorological Institute), H. Gregow (Finnish Meteorological Institute)

Since June 2017, novel six-week climatic forecasts are produced operationally at the Finnish Meteorological Institute (FMI) in CLIPS project (CLImate services supporting Public activities and Safety, http://clips.fmi.fi/?lang=en). The main emphasis is to support the Finnish public in planning their activities by co-designing and piloting the products together with the end-users community. It is clear that the provision of usable forecasts especially at high-latitudes is a challenging task. To examine the accuracy and usability of the developed products, essential part of the work is the verification of the forecasts for which the ECMWF reanalysis data plays an important role.

Variations of drought index with different reference periods

Author Myoung-Jin Um

Affiliation Yonsei University

Co-authorsY. Kim (Yonsei University), D. Park (Konkuk University)

The objective in this study is understanding how much the drought indices are changed due to the different reference periods. We focused on the effects of drought characteristics, such as trends and frequency, for historical periods (1901-2014) with the standard precipitation evapotranspiration index (SPEI) and used the datasets of the climate research unit (CRU) and the University of Delaware (UDEL).

We chose the three cases of reference periods, such as Ref 1 (1901–2014), Ref 2(1901-1957 and 1958–2014) and Ref 3 (1901-1957) and estimated the SPEI to investigate the statistical differences. We found that drought characteristics, particularly the severity and spatial extent, were different depending on the reference periods. Although we used only two global datasets (CRU and UDEL), we suggest that the reference period should be carefully chosen to estimate the statistical drought indices.

Acknowledgement This study was supported by the Korea Meteorological Administration R&D Program under Grant KMIPA 20156180 and by the Basic

Section 5


model data production and preliminary results of the validations of the global 3km resolution wind resolution based in ERA Interim and ERA5 (reduced sample) downscaling.

world’s wind resource ant to produce the global mesoscale layer of wind and other meteorological variables.

A further downscaled will be conducted by DTU to under the kilometre resolution using and WAsP model and derived generalized wind climatologies. The atlas will have an interim version to be released in November 2017 which will be built using ERA Interim Reanalysis as large scale conditions. The final version which is scheduled to go live by the end of 2018 will incorporate ERA5 Copernicus Climate Change Service (C3S) Reanalysis as drivers.

The modelling will seamlessly interact with the existing GWA, helping develop a free access wind resource tool. At the same time the data will deliver real change on the ground, helping policy makers and project developers in developing countries get projects built.

The engagement will also see the consortium deliver a wide spectrum of development support in a number of emerging economies, from country-level analysis and wind development zone identification through to individual bankable site assessment and due diligence review.

The presentation will provide a description of the methodological approach based on the use reanalysis and mesoscale modeling technology and status of the project development. Focus will be given to the mesoscale

World Bank New Global Wind Atlas project powered by Copernicus Reanalysis

Author Gil Lizcano

Affiliation Vortex

Co-authorsO. Lacava, (Vortex), P. Casso, (Vortex), A. Bosch, (Vortex), A. Hahmann, (DTU), J. Badger, (DTU), R. Whiting, (Everoze)

Good wind data is critical to getting more wind projects built, and in turn helping to ensure access to affordable, reliable, sustainable and modern energy for all. With this intention, World Bank (WB), through the ESMAP program, launched several initiatives to improve access to quality of wind and solar resource information and, hence, to boost new renewable energies markets in developing countries. As part of this effort, a global wind atlas master plan has been designed by the WB in partnership with Danish Technology University (DTU).

The project will update existing DTU Global Wind Atlas (GWA) with an improved modeling stream which will incorporate latest Reanalysis datasets and a complete mesoscale model downscaling. The new GWA project will undertake a global level meso-scale modelling to 3km resolution which will be be achieved with WRF atmospheric modelling stream. Mesoscale modellers Vortex will be responsible to map the

Section 5


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5th International Conference on Reanalysis (ICR5) 13–17 November 2017, Rome

Documents

5th International Conference on Reanalysis (ICR5) · 2017-11-03 · data for climate reanalyses Leopold Haimberger (University of Vienna) 2.30–2.45pm O.05 The Copernicus Climate